News & Events
The 1119433 th visit
Schedule
Beijing Time: 2017-09-26 05:24:13

Seminar

[2017.08.29] Lecture: A matrix-analytic approach to Markov-modulated Brownian motion, Prof. Guy Latouche

Speaker: Prof. Guy Latouche, Université Libre de Bruxelles, Belgium

Venue: Room 3-620, FIT Building, Tsinghua University

Time: 2017-8-29 15:00

Abstract:

Ramaswami has shown in 2013 that standard Brownian motion is the limit of a family of two-phase fluid queues with increasing rates of transition from one phase to the other. This has motivated us to investigate Markov-modulated Brownian motions (MMBMs) from a matrix-analytic point of view, starting from a Markov-regenerative approach and using fast-switching fluid queues as a tool to determine the required characteristics. Fluid queues, are a particular family of MMBMs characterized by the fact that the evolution is piecewise linear without Brownian noise. A key consequence is that stochastic fluid queues are amenable to Kolmogorov-type analysis. We present here a summary of the idea behind the technique and of the results obtained so far.

Prof. Guy Latouche

Guy Latouche received the Ph.D. degree in Mathematics from the Université Libre de Bruxelles (ULB) in 1976. He has mostly taught classes on stochastic processes and their applications at ULB, and he has extensively visited colleagues abroad: at the University of Adelaide, Bellcore, Central South University, the University of Delaware, the University of Melbourne, the University of Pisa, and the Tokyo Institute of Technology. His research activity includes various aspects of computational probability: he has participated in the development of matrix-analytic methods for the analysis of Markov models, with applications in queueing theory, telecommunication systems, fluid queues, branching processes and ruin theory. He has also shown a minor, but recurrent, interest for nearly completely decomposable systems. He has co-authored three books, edited ten monographs, and has more than 100 scientific papers published in the refereed literature; he has successfully supervised 10 PhD students and been co-chair of the programme committee for several international conferences of high standing. He has been Dean of the Facult Libre des Sciences at ULB.

Guy Latouche教授进行讲座

Original Size: [1]

[2017.06.02] Lecture: Seeking autonomy in multi-agent system optimization: it's not that easy..., Prof. Christos G. Cassandras

Speaker: Prof .Christos G. Cassandras, Boston University

Venue: Room511, Centeral Main Building, Tsinghua University

Time: 2017-06-02 10:00

Abstract:

A unifying optimization-based framework will be presented which encompasses most commonly encountered cooperative multi-agent system problems, including coverage control, consensus, formation control, and persistent monitoring. We will then address the issue of identifying conditions under which a centralized solution to such problems can be recovered in a decentralized manner, thus leading to autonomousagents. For parametric optimization problems, conditions and explicit distributed algorithms can be derived. For dynamic optimization problems, however, decentralization is particularly challenging due to the time-varying nature of the agent network and the fact that agents take actions depending on interactions with the environment (targets) which cannot be easily shared through the agent network. For the class of persistent monitoring problems studied in a one-dimensional setting, it has been shown that a complete optimal solution can be obtained through an event-driven centralized gradient-based algorithm using Infinitesimal Perturbation Analysis (IPA). We will show that the IPA gradient can be recovered in an “almost distributed” manner in which each agent optimizes its trajectory based on local information, except for one event requiring communication from a non-neighbor agent.

Prof. Christos G. Cassandras

Christos G. Cassandras is Distinguished Professor of Engineering at Boston University. He is Head of the Division of Systems Engineering, Professor of Electrical and Computer Engineering, and co-founder of Boston University’s Center for Information and Systems Engineering (CISE). He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, cooperative control, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published about 400 refereed papers in these areas, and six books. He has guest-edited several technical journal issues and serves on several journal Editorial Boards. In addition to his academic activities, he has worked extensively with industrial organizations on various systems integration projects and the development of decision-support software. He has most recently collaborated with The MathWorks, Inc. in the development of the discrete event and hybrid system simulator SimEvents. Dr. Cassandras was Editor-in-Chief of the IEEE Transactions on Automatic Control from 1998 through 2009 and has also served as Editor for Technical Notes and Correspondence and Associate Editor. He is currently an Editor of Automatica. He was the 2012 President of the IEEE Control Systems Society (CSS). He has also served as Vice President for Publications and on the Board of Governors of the CSS, as well as on several IEEE committees, and has chaired several conferences. He has been a plenary/keynote speaker at numerous international conferences, including the American Control Conference in 2001 and the IEEE Conference on Decision and Control in 2002 and 2016, and has also been an IEEE Distinguished Lecturer. He is the recipient of several awards, including the 2011 IEEE Control Systems Technology Award, the Distinguished Member Award of the IEEE Control Systems Society (2006), the 1999 Harold Chestnut Prize (IFAC Best Control Engineering Textbook) for Discrete Event Systems: Modeling and Performance Analysis, a 2011 prize and a 2014 prize for the IBM/IEEE Smarter Planet Challenge competition (for a “Smart Parking” system and for the analytical engine of the Street Bump system respectively), the 2014 Engineering Distinguished Scholar Award at Boston University, several honorary professorships, a 1991 Lilly Fellowship and a 2012 Kern Fellowship. He is a member of Phi Beta Kappa and Tau Beta Pi. He is also a Fellow of the IEEE and a Fellow of the IFAC.

Christos G. Cassandras教授进行讲座

Original Size: [1]

[2017.05.12] Lecture: Multi-Agent Networked Systems, Prof. Tamer Başar

Speaker: Prof. Tamer Başar, Center for Advanced Study (CAS), University of Illinois

Venue: Room 1-315, FIT Building, Tsinghua University

Time: 2017-05-12 10:00

Abstract:

The recent emergence of multi-agent networks in general, and cyber-physical systems in particular, has brought about several non-traditional and non-standard requirements on strategic decision-making, thus challenging the governing assumptions of traditional control and game theory. Some of these requirements stem from factors such as: (i) limitations on memory, (ii) limitations on computation and communication capabilities, (iii) heterogeneity of decision makers (machines versus humans), (iv) heterogeneity and sporadic failure of channels that connect the information sources (sensors) to decision units (strategic agents), (v) limitations on the frequency of exchanges between different decision units and the actions taken by the agents, (vi) operation being conducted in a possibly hostile environment where disturbances are controlled by adversarial agents, (vii) lack of cooperation among multiple decision units, (viii) lack of a common objective shared by multiple decision stations, and (ix) presence of multiple layers in the topologies of the underlying networks. These all lead to substantial degradation in performance and loss in efficiency if appropriate mechanisms are not in place. The talk will identify the underlying challenges, particularly those that are brought about by the adversarial and non-cooperative nature of the environment, discuss some solutions, and also dwell on the research opportunities this broader framework creates for communication, control, networking, and game theory. In this context, also issues of network resilience, reliability and security will be discussed, with some specific applications in networks with static and dynamic (mobile) nodes, with adversary-inflicted topological changes.

Prof. Tamer Başar

Tamer Başar has been with the University of Illinois at Urbana-Champaign since 1981, where he currently holds the academic positions of Swanlund Endowed Chair; Center for Advanced Study Professor of Electrical and Computer Engineering; Professor, Coordinated Science Laboratory; Professor, Information Trust Institute; and Affiliate Professor, Mechanical Sciences and Engineering. Since 2014, he also holds the administrative position of Director of the Center for Advanced Study, and prior to that he was the Director of the Beckman Institute for Advanced Science and Technology. He received his BSEE degree from Robert College (Istanbul), and MS, MPhil, and Ph.D. degrees from Yale University (New Haven). Dr. Başar is a member of the US National Academy of Engineering and the European Academy of Sciences; Fellow of IEEE, IFAC, and SIAM; a past president of the IEEE Control Systems Society (CSS), the founding (and past) president of the International Society of Dynamic Games (ISDG), and a past president of the American Automatic Control Council (AACC). He has received several awards and recognitions over the years, including the highest awards of IEEE CSS, IFAC, AACC, and ISDG, the IEEE Control Systems Technical Field Award, Medal of Science of Turkey, and a number of international honorary doctorates and professorships, including chaired professorship at Tsinghua University. He has over 800 publications in systems, control, communications, optimization, networks, and dynamic games, including books on non-cooperative dynamic game theory, robust control, network security, wireless and communication networks, and stochastic networks. He is editor of several book series.

Basar教授进行讲座
Basar教授进行讲座

Original Size: [1] [2]

[2017.03.17] Lecture: From RG-Factorizations of Stochastic Models to Black Hole Effect in Big Networks, Prof. Quanlin Li

Speaker: Prof. Quan-Lin Li, School of Economics and Management, Yanshan University

Venue: Room 3-620, FIT Building, Tsinghua University

Time: 2017-03-17 10:00

Abstract:

This talk contains two parts: The first one is to introduce our research on numerical computation in general stochastic models. Our purpose is to extend and generalize the matrix-geometric solution by Marcel F. Neuts to be able to deal with more general Markov processes due to various needs from more and more practical stochastic systems. To that end, we use the censoring technique to set up two types of (abbreviated as UDL-type and LDU-type) RG-factorizations for any irreducible Markov process and further for Markov reward processes and Markov decision processes. Our results are simple and beautiful, and also they are easily applicable to computation of the steady-state probability vectors of general Markov processes by means of the UDL-type RG-factorization as well as calculation of transient performance measures of stochastic models in terms of the LDU-type (and UDL-type) RG-factorizations. Notice that our research largely improves Neuts’ matrix-geometric solution into a new and unified framework in terms of applying the UDL-type and LDU-type RG-factorizations. For this, some detailed information is given in my book: Constructive Computation in Stochastic Models with Applications: The RG-Factorizations, Springer, 2010; and its Springer homepage: http://link.springer.com/book/10.1007/978-3-642-11492-2 .The second part of this talk is to introduce our works on Nonlinear Markov Processes in Big Networks through mean-field theory and RG-factorizations. We have applied the mean-field theory as well as the RG-factorizations to discussing nonlinear Markov processes from some practically large-scale stochastic systems including supermarket models, work stealing models, bike-sharing systems, healthcare systems and so forth. For some practical Big (Economy) Networks with active control mechanisms, we found that Black Hole Effect is a basic phenomenon. To understand the black hole effect, we develop three key topics: (a) Metastability, multiple stable domains, and cross-domain movement; (b) existence of black hole effect, and metrology of black hole effect; and (c) loss of resources from black hole effect and from multiple stable domains. We establish useful relationship between network efficiency and network benefit under artificial control mechanisms. Therefore, our results provide some irregular characteristics and insights in the study of large-scale stochastic systems, and they may be useful in design, optimization, control and management of many real applied systems.

Prof. Quanlin Li

Quanlin Li is a professor of the School of Economics and Management Sciences at Yanshan University. Prof Li recieved and his PhD in Institute of Applied Mathematic at Chinese Academy of Sciences. Prof. Li has published over 50 SCI cited papers.Prof. Li's research interests include stochastic models, the mean-field approximation in supermarket models, queueing analysis in work stealing models, the censoring technique, crucial generalization for the matrix-analytic methods, QBD processes and RG-factorizations.

[2016.12.14] Lecture: Modeling Tiered Security Screening Systems at Airports, Prof. Zhe George Zhang

Speaker: Prof. Zhe George Zhang, Western Washington University, USA

Venue: Room 3-620, FIT Building, Tsinghua University

Time: 2016-12-14 10:00

Abstract:

We analyze a tiered airport security checkpoint at an international airport. In such a system, passengers can be classified into three categories based on the security intelligence. A two-dimensional Markov process and a Markov modulated Poisson process (MMPP) are utilized to model these type inspection systems. We first develop the formulas for the performance evaluation under a given passenger allocation policy with conditional capacity sharing in the tiered security-check system. Due to the complexity of the system and the multiple decision variables, a near-optimum inspection policy is determined by the simulated annealing method. By comparing the proposed system with the two conventional security-check systems (non-tiered and tiered without capacity sharing), we find that the tiered system with conditional capacity sharing could improve the customer service without compromising the security quality. This is a joint on-going research project with Paul Hsing Luh and P.K. Huang of National Chengchi University.

Prof. Zhe George Zhang

Zhe George Zhang is a professor of Management Science in the Department of Decision Sciences at Western Washington University and a professor of Operations Management in Beedie School of Business at Simon Fraser University. He is also visiting professor of Sauder School of Business at the University of British Columbia. Dr. Zhang received his BS in Computer Science and MA in Economics from Nankai University, China; his MBA from the Schulich School of Business at York University; and his PhD in Operations research from the University of Waterloo. Professor Zhang has published over 80 papers in prestigious journals such as Management Science, Operations Research, Manufacturing & Service Operations Management, Production and Operations Management, IIE Transactions, IEEE Transactions, Queueing Systems, Journal of Applied Probability. Professor Zhang's research interests include queueing theory and applications and stochastic models for manufacturing and service systems. The main theme of his research is to bridge the gap between theory and application, obtaining unobservable and sometimes counter-intuitive but significant/practical management insights via modelling and quantitative analysis. Currently, he is particularly interested in the quantitative and economic analysis of the congestion problems in urban/mass transportation networks, health/medical care systems, and public service systems with both customer service quality and security concerns. Co-authored with N. Tian, his research monograph entitled Vacation Queueing Models-Theory and Applications has been published in 2006 by Springer Science. This is the first book that discusses both single and multiple server queueing systems with vacations. Professor Zhang is an associate editor of INFOR and is on the editorial board of several international journals.

[2016.10.28] Lecture: Application of the Theory of Constraints in Manufacturing Systems: The Myths and Clarification, Prof. Kan Wu

Speaker: Prof. Kan Wu, Nanyang Technological University, Singapore

Venue: Room 3-620, FIT Building, Tsinghua University

Time: 2016-10-28 10:00

Abstract:

The theory of const raints was proposed in the mid-1980s and has significant impact on the productivity improvement in manufacturing systems. While it is intuitive and easy to understand, its conclusions are mainly derived in deterministic settings or based on the first moment results. Since production systems are stochastic in general, some of its conclusions are not rigorous and have to be modified. In this study, we show that the process of ongoing improvement may lead to unfavorable outcomes and the throughput bottleneck should be planned on certain types of machines. Specifically, if a system has no bottleneck, every station will be a bottleneck. Furthermore, through capturing the dependence among stations, we show that improving the variability of a frontend machine in a production line can be more effective than improving the variability of a throughput bottleneck.

Prof. Kan Wu

Kan Wu is an assistant professor in the School of Mechanical & Aerospace Engineering at Nanyang Technological University. He received the B.S. degree from National Tsinghua University, M.S. degree from University of California at Berkeley, and Ph.D. degree in Industrial and Systems Engineering from Georgia Institute of Technology. He has ten years of experience in the semiconductor industry, from a consultant to an IE manager. Before joining NTU, he was the CTO and founding team member of a startup company in the US. His PhD dissertation was awarded the 3rd place for the IIE Pritsker Doctoral Dissertation Award. His current research interests are primarily in the areas of queueing theory, with applications in the performance evaluation of supply chains and manufacturing systems.

[2016.06.17] Lecture: Formal design of distributed cooperative systems, Prof. Hai Lin

Speaker: Prof. Hai Lin, University of Notre Dame, USA

Venue: Room 407, Central Main Building, Tsinghua University

Time: 2016-06-17 10:00

Abstract:

A common challenge in our future engineered system design, such as power grids, intelligent transportation networks and Internet of Things, is how to make a large number of distributed systems work together in a reliable and efficient manner. Existing methods are either only suitable for small scale systematic synthesis, oversimplifying the nodal dynamics, lack of performance guarantees or fail to adapt to changing environments. This motivates our research aiming at a scalable, correct-by-construction formal design methodology for distributed cooperative systems. In particular, we focus on a formal design of multi-robot systems that can guarantee the accomplishment of high-level team missions through automatic synthesis of local coordination mechanisms and control laws. Our basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to local synthesis problems for individual robots, and then solving these local synthesis problems by composing predesigned and verified reactive motion/action primitives of robots. Multidisciplinary approaches combining control theory, machine learning and computational verification are utilized to achieve this goal. The developed theory will enable robots in the team to cooperatively learn their individual roles in a mission, and then automatically synthesize local task and mission plans to fulfill their subtasks. A salient feature of the proposed method lies on its ability to handle environmental uncertainties and un-modeled dynamics, as we do not require an explicit model of the transition dynamics of each agent and their interactions with the environment. In addition, the design is on-line and reactive enabling the robot team to adapt to changing environments and dynamic tasking.

Prof. Hai Lin

Hai Lin is currently an associate professor at the Department of Electrical Engineering, University of Notre Dame, where he got his Ph.D. in 2005. Before returning to his alma mater, Hai has been working as an assistant professor in the National University of Singapore from 2006 to 2011. Dr. Lin's teaching and research interests are in the multidisciplinary study of the problems at the intersections of control, communication, computation, machine learning and computational verification. His current research thrust is on cyber-physical systems, multi-robot cooperative tasking, and human-machine collaboration. Hai has been served in several committees and editorial board, including IEEE Transactions on Automatic Control. He is currently serving as the Chair for the IEEE CSS Technical Committee on Discrete Event Systems. He served as the Program Chair for IEEE ICCA 2011, IEEE CIS 2011 and the Chair for IEEE Systems, Man and Cybernetics Singapore Chapter for 2009 and 2010. He is a senior member of IEEE and a recipient of 2013 NSF CAREER award.

[2016.06.08] Lecture: The Measure-valued Differentiation Approach to Gradient Estimation, Prof. Bernd Heidergott

Speaker: Prof. Bernd Heidergott, Vrije Universiteit Amsterdam

Venue: Room 1-312, FIT Building, Tsinghua University

Time: 2016-06-08 14:00

Abstract:

Measure-valued differentation (MVD) is next to IPA and the Score Fuction method one of the three main techniques for estatblishing unbiased gradient estimators. We give a gentle introduction into MVD and illustrate its relation with IPA and the Score Function.

Prof. Bernd Heidergott

Bernd Heidergott is Chair of Stochastic Optimization at the Department of Econometrics and Operations Research at the Faculty of Economics and Business Administration of the Vrije Universiteit Amsterdam. At this university he is program director of the bachelor and master program Econometrics and Operations Research, and member of the board of the Amsterdam Business Research Institute (ABRI). Before joining the VU University Amsterdam he held post-doc positions at Erasmus University Rotterdam, Eindhoven University of Technology, Delft University of Technology, and EURANDOM. He is author of two monographs and more than 40 international journal papers. Bernd Heidergott is ABRI Research Fellow, and Tinbergen Institute Fellow.

[2016.06.08] Lecture: Stochastic Path Optimization for Robotic Bees using Cloud Computing, Prof. Felisa Vazquez-Abad

Speaker: Prof. Felisa Vazquez-Abad, City University of New York, USA

Venue: Room 1-312, FIT Building, Tsinghua University

Time: 2016-06-08 10:00

Abstract:

We study the problem of dynamic routing of robotic bees towards the hive, with the intended purpose of minimizing the time it takes for all the bees to arrive at the destination. Due to uncertainty in position measurements, the stochastic problem cannot ensure collision-free paths. Cloud computing is assumed when bees have antennas that can sense the hive signals, and we explain the challenges in estimation and control in order to successfully guide the robotic bees.

Prof. Felisa Vazquez-Abad

Felisa Vazquez-Abad is currently Professor of Computer Science at Hunter College. Her research lies at the intersection between mathematics, engineering and computer science. She is mainly interested in the optimization of complex systems under uncertainty, primarily to understand, control and / or build efficient self-regulated learning systems. She obtained a B.Sc. in Physics in 1983 and a M.Sc. in Statistics and Operations Research in 1984 from the Universidad Nacional Autónoma de México. In 1989 She obtained a Ph.D. in Applied Mathematics from Brown University. After four years doing postdoctoral research at Brown University and later at the INRS-Telecommunications in Montreal, Canada, she became a professor of computer science at Université de Montréal, Canada in 1993. In 2004 she became a professor of mathematics and statistics at the University of Melbourne, Australia, until 2009, when she moved to CUNY.

[2016.06.07] Lecture: Analysis of Markov Influence Networks, Prof. Bernd Heidergott

Speaker: Prof. Bernd Heidergott, Vrije Universiteit Amsterdam

Venue:Room 1-415, FIT Building, Tsinghua University

Time: 2016-06-07 14:00

Abstract:

Since the early paper by Paul Schweitzer on perturbation analysis published in 1968, perturbation analysis of Markov chains has attracted much attention in the literature. Unfortunately, known perturbation bounds are rather limited in their range of applicability. Specifically, the relative error of the known perturbation bounds fails to tend to zero as the size of the perturbation tends to zero. We will introuduce a new bound that overcomes this drawback. We illustrate our findings by means of a realistic application to a problem in queuing. We identify a new area of applications of perturbation bounds to stabilty analysis of mixtures of stable chains with unstable chains, which, as we belive, opens a door to a very interesting line of research.

Prof. Bernd Heidergott

Bernd Heidergott is Chair of Stochastic Optimization at the Department of Econometrics and Operations Research at the Faculty of Economics and Business Administration of the Vrije Universiteit Amsterdam. At this university he is program director of the bachelor and master program Econometrics and Operations Research, and member of the board of the Amsterdam Business Research Institute (ABRI). Before joining the VU University Amsterdam he held post-doc positions at Erasmus University Rotterdam, Eindhoven University of Technology, Delft University of Technology, and EURANDOM. He is author of two monographs and more than 40 international journal papers. Bernd Heidergott is ABRI Research Fellow, and Tinbergen Institute Fellow.

[2016.05.19] Lecture: From Energy-Smart Buildings to Our Ambition, Prof. Peter B Luh

Speaker: Dr. Peter B Luh, Professor of University of Connecticut and Chair Professor of CFINS Tsinghua University.

Venue: Room 511, Central Main Building, Tsinghua University

Time: 2016-05-19, 10:00 am

Abstract:

The increasing ecological burden of our lifestyle is threatening the integrity of the entire biomes, and our global environmental footprint exceeds the world’s regeneration capacity by about 30%. Considering that energy use in buildings represents more than 40% of global energy consumption and that humans spend 90% of the time indoors, technologies enabling smarter buildings can lead to significant reductions in energy consumption and greenhouse gas emissions, and produce a comfortable, efficient and sustainable environment. The above can be achieved through smart building design, advanced automation, and intelligent computing/communication technologies to efficiently design, operate, monitor, and maintain buildings. In particular, integrated building energy management will be highlighted in the talk. The goal is to demonstrate that smart buildings are a fertile problem context for research and development. We will then briefly indicate how the same modeling and optimization framework can be extended to tackle another important issue of grid integration of intermittent renewable generation (e.g., using wind and solar), and how Industry 4.0 can serve as enabling technologies for intelligent automation. We will have time for questions and answers on technical questions and beyond.

Prof. Peter B Luh

Peter B. Luh received his B.S. in Electrical Engineering from National Taiwan University, M.S. in Aeronautics and Astronautics from M.I.T., and Ph.D. in Applied Mathematics from Harvard University. He has been with the University of Connecticut since 1980, and currently is the SNET Professor of Communications & Information Technologies. He was the Head of UConn’s Department of Electrical and Computer Engineering from 2006 to 2009. He is also a member of the Chair Professors Group, Center for Intelligent and Networked Systems (CFINS) in the Department of Automation, Tsinghua University, Beijing, China. Professor Luh is a Fellow of IEEE, and is a member of IEEE TAB Periodicals Committee. He was the VP of Publications of the Robotics and Automation Society (2008-2011), the founding Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering (2003-2007), and the Editor-in-Chief of IEEE Transactions on Robotics and Automation (1999-2003). He received IEEE Robotics and Automation Society 2013 Pioneer Award for his pioneering contributions to the development of near-optimal and efficient planning, scheduling, and coordination methodologies for manufacturing and power systems. His research interests include smart grid, smart buildings and intelligent manufacturing systems.

[PPT file download]

[2015.12.11] Lecture: Mean-variance problems for continuous-time MDPs, Prof. Xianping Guo

Speaker: Prof. Xianping Guo, Sun Yat-Sen University

Venue: Room 3-620, FIT Building, Tsinghua University

Time: 2015-12-11 13:30

Abstract:

Following from the philosophy of Nobel laureate Markowitz's mean-variance portfolio selections, we introduce a mean-variance optimization problem for continuous-time Markov decision processes. Then, we will 1) show the existence of a g-mean-variance optimal policy that minimizes the variance over the set of policies attaining a given mean performance g, 2) give the algorithms for computing the g-variance value function and an g-mean-variance optimal policy, 3) explicitly solve two examples for illustrating our main results, and 4) provide some unsolved problems.

Prof. Xianping Guo

Prof. Xianping Guo is a full professor of the school of mathematics and computing science, Sun Yat-Sen Univeristy, Guangzhou, China. His main research interest is about the stochastic optimization, especially about the Markov decision processes. He also serves as Associate Editor in several premier academic journals, such as "Advances in Applied Probability", "Journal of Applied Probability", etc.

[2015.11.12] Lecture: Sensors & actuators in control of distributed parameter systems, Prof. Kirsten Morris

Speaker: Prof. Kirsten Morris, University of Waterloo, Canada

Venue: Room 407, Main Building, Tsinghua University

Time: 2015-11-12 10:00

Abstract:

For control of systems that vary in space, there is generally choice in the type of actuator and sensors used and also their locations. Performance depends on the location of controller hardware, the sensors and actuators. The best locations may be different from those chosen based on physical intuition. Since it is often difficult to move hardware, and trial-and-error may not be effective when there are multiple sensors and actuators, analysis is crucial. A mechatronic approach, where controller design is integrated with actuator location, can lead to better performance without increased controller cost. Similarly, better estimation can be obtained with carefully placed sensors. Proper placement when there are disturbances present is in general different from that appropriate for reducing the response to an initial condition, and both are quite different from locations based on optimizing controllability or observability. The choice of actuator and sensor and modelling of the control hardware are also factors in controller design. The models for these systems will be coupled ordinary/partial differential equations (PDE's). Approximations to the governing equations, often of very high order, are required and this complicates both controller design and optimization of the hardware locations. Numerical algorithms and issues will be briefly discussed.

Prof. Kirsten Morris

Prof. Kirsten Morris’ research interests are systems modelled by partial differential equations and also systems, such as smart materials, involving hysteresis. In addition to her research articles on this work, she has written an undergraduate textbook "Introduction to Feedback Control", and was editor of the book “Control of Flexible Structures”. Professor Morris is a member of the Applied Mathematics Department at the University of Waterloo and is cross-appointed to the Department of Mechanical & Mechatronics Engineering. From 2005-2008 she was Associate Dean for Graduate Studies & Research in the Faculty of Mathematics. She was an associate editor with the IEEE Transactions on Automatic Control and also SIAM Journal on Control & Optimization and is a member of the editorial board of the SIAM book series Advances in Design & Control. Prof. Morris has served as a member of the IEEE Control System Society Board of Governors since 2010 and is currently vice-president, technical activities.

[2015.10.22] Lecture: Large Dynamic Range System Identification, Dr. James Welsh

Speaker: James Welsh

Venue: Room 407, Main Building, Tsinghua University

Time: 2015-10-22 10:00

Abstract:

A well known difficulty in frequency domain system identification over a large bandwidth is the ill-conditioning of the normal matrix. This typically manifests itself as poor or erroneous estimates. Several methods have been proposed in the literature for addressing this issue. However, none appear to give an entirely satisfactory solution. Here we present a novel technique, utilising particular basis functions, aimed specifically at improving the numerical properties of the least squares normal matrix in parameter estimation over a large dynamic range. We show that, under some mild assumptions, the achieved condition number for the proposed method is actually independent of the frequency range. Several examples are presented showing the superior performance of the proposed method when applied to large dynamic range estimation problems.

James Welsh

James Welsh was born in Maitland, Australia. He received the B.E. degree (Hons. I) in electrical engineering from The University of Newcastle, Australia. Dr. Welsh received his PhD in 2004, which studied ill-conditioning problems arising in system identification, from the same university. During the last several years, he has been actively involved in research projects at the Centre for Complex Dynamic Systems and Control, The University of Newcastle, involving System Identification, Model Predictive Control and Powertrain Control. His research interests span across system identification and control system design. Recent projects have taken him into the modelling and simulation of biological systems and also areas of rehabilitation. He is currently with the School of Electrical Engineering and Computer Science, The University of Newcastle.

[2015.10.12] Lecture: Plug-and-Play methods for the monitoring of Large-Scale Systems, Dr. Francesca Boem

Speaker: Francesca Boem

Venue: Room 407, Main Building, Tsinghua University

Time: 2015-10-12 14:00

Abstract:

Large-Scale Systems (LSS) attract a significant and steadily growing interest in academia and industry. These systems are characterized by a large number of states and inputs, are generally spatially distributed, and are modeled as the interaction of many subsystems coupled through physical or communication relationships. Reliability is a key requirement in systems design and the development of distributed methods for fault diagnosis is an emergent important topic. When dealing with the monitoring of LSSs, in fact, centralized architectures can be not adequate due to computational, communication, scalability and reliability limits. An alternative is offered by the adoption of decentralized and distributed approaches. Furthermore, LSSs can often have a dynamic structure that changes along the time. For this reason, a novel requirement is the design of monitoring architectures able to be robust to the changes that may happen in the dynamic structure of the LSS. In this talk, I will present a distributed model-based fault detection and isolation architecture and I will explain how to use it in Plug-and-Play scenarios for a fault-tolerant control scheme.

Francesca Boem

Francesca Boem received the Laurea (M.Sc.) degree (cum laude) in Management Engineering in 2009 and the Ph.D. degree in Information Engineering in 2013 from the University of Trieste, Italy. She was Post-Doc at the Department of Engineering and Architecture at the University of Trieste from 2013 to 2014 with the Automation Group and with the Machine Learning Group. Since 2014, she is Research Associate at the Department of Electrical and Electronic Engineering, Imperial College London, UK, with the Control and Power Research Group. She visited the Institute for Human-Machine Communication at the Technical University of Munich, Germany, in 2010, and the ACCESS Linnaeus Center, KTH Royal Institute of Technology, Sweden, in 2013. She cooperated with the R&D department of Danieli Automation SpA, Buttrio (UD), Italy. She has authored and co-authored several papers published in international journals and conference proceedings. Her current research interests include distributed fault diagnosis methods for large-scale networked systems and distributed estimation methods for sensor networks.

[2015.10.12] Lecture: Approximate solutions for differential games, Dr. Thulasi Mylvaganam

Speaker: Thulasi Mylvaganam

Venue: Room 407, Main Building, Tsinghua University

Time: 2015-10-12 10:00

Abstract:

A wide variety of problems can be described and studied using the framework provided by differential game theory. We focus on a class of nonzero-sum, infinite horizon differential games. Obtaining solutions to such problems involves solving a system of coupled partial differential equations and, in general, closed-form solutions to these cannot be readily obtained. For this reason, it is often necessary to settle for approximate solutions. A systematic method of constructing approximate solutions to the class of differential games, without solving partial differential equations, is presented and applied to a variety of numerical examples. Furthermore, through the introduction of these examples we highlight some possible areas of applications for the developed theory. Notable examples which will be encountered are a competitive biological system, multi-agent systems and power systems.

Thulasi Mylvaganam

Thulasi Mylvaganam was born in Bergen, Norway, in 1988. She received the M.Eng. degree in electrical and electronic engineering from Imperial College London in 2010 and the Ph.D. degree with the Control and Power Research Group in the Department of Electrical and Electronic Engineering, Imperial College London in 2014. She is currently a Postdoctoral Research Associate at the Department of Electrical and Electronic Engineering, Imperial College London. Her research interests include multi-agent systems and differential games and their applications.

[2015.09.22] Lecture: Fundamental Trade-offs in Robust Control with Heterogeneous Uncertainty, Prof. Tamer Basar

Speaker: Prof. Tamer Basar

Venue: Room 1-312, FIT Building, Tsinghua University

Time: 2015-09-22 14:30-15:30

Abstract:

The new paradigm of networked control systems, where the feedback loop is closed over heterogeneous networks, has opened up a vast number of opportunities for applications in different fields while creating also a number of challenges with regard to reliability, robustness, and security of control operations. This plenary talk will address these challenges, where networks providing sensor measurements to controller(s) and those carrying control signals to the plant as well as the plant itself are vulnerable to stochastic as well as adversarial disturbances and sporadic failure of channel connectivity. The question of interest is the extent to which the plant, measured in terms of a performance metric, can tolerate such disturbances and failures, which themselves are also quantified in terms of some appropriate metrics.

Following a general overview of networked control problems, the talk will focus on linear-quadratic systems, with norm-bounded deterministic (adversarial) disturbance inputs and hybrid stochastic uncertainty that impacts network channels, which is characterized by additive Gaussian noise and Bernoulli type failures. Explicit results for both the estimation problem and the control problem will be discussed under the TCP (Transmission Control Protocol) type information structure (which leads to certainty-equivalance, but not to separation of estimation and control), and the trade-offs between control performance, disturbance energy, and channel failure rates (that is, channel reliability) will be quantified. Under the UDP (User Datagram Protocol) type packet loss acknowledgement process, on the other hand, there is no certainty-equivalance, but still some trade-off results can be obtained. The talk will conclude with a discussion of future directions of research in this area and the challenges that lie ahead.

Prof. Tamer Basar

Tamer Basar was born in Istanbul, Turkey, on January 19, 1946. He received B.S.E.E. degree from Robert College, Istanbul, in 1969, and M.S., M.Phil, and Ph.D. degrees in engineering and applied science from Yale University, in 1970, 1971 and 1972, respectively. After stints at Harvard University, Marmara Research Institute (Gebze, Turkey), and Bogazi?i University (Istanbul), he joined the University of Illinois at Urbana-Champaign (UIUC) in 1981, where he is with the Department of Electrical and Computer Engineering, is the Director of the Center for Advanced Study, and carries the academic titles of Swanlund Endowed Chair, Center for Advanced Study Professor of Electrical and Computer Engineering, Professor at the Coordinated Science Laboratory, Professor with the Information Trust Institute, and Affiliate Professor at the Department of Mechanical Science and Engineering. He is a Chair Professor and the Chief Scientist of the Center for Intelligent and Networked Systems (CFINS), Tsinghua University. He has spent sabbatical years at Twente University of Technology (the Netherlands; 1978-79), and INRIA (France; 1987-88, 1994-95).

[2015.09.18] Lecture: Dynamic Non-Cooperative Game Theory, Prof. Tamer Basar

Speaker: Prof. Tamer Basar

Venue: Room 1-312, FIT Building, Tsinghua University

Time: 2015-09-18&21 14:00-16:00

Abstract:

This couple of seminars, two hours each, constitutes a continuation of the short course I had given earlier in May 2015 on non-cooperative game theory. The two topics to be covered involve dynamic Nash equilibria and dynamic Stackelberg equilibria in dynamic games in discrete time. Counterparts in continuous time, for so-called nonzero-sum differential games will also be discussed, but briefly. The role of information structure in such dynamic games will be a centerpiece in the presentations. For the benefit of those who were not able to attend the short course in May, I will make these lectures self-contained. A background in dynamic optimization (such as optimal control) will be sufficient. An outline of this series of lectures follows.

Prof. Tamer Basar

Tamer Basar was born in Istanbul, Turkey, on January 19, 1946. He received B.S.E.E. degree from Robert College, Istanbul, in 1969, and M.S., M.Phil, and Ph.D. degrees in engineering and applied science from Yale University, in 1970, 1971 and 1972, respectively. After stints at Harvard University, Marmara Research Institute (Gebze, Turkey), and Bogazi?i University (Istanbul), he joined the University of Illinois at Urbana-Champaign (UIUC) in 1981, where he is with the Department of Electrical and Computer Engineering, is the Director of the Center for Advanced Study, and carries the academic titles of Swanlund Endowed Chair, Center for Advanced Study Professor of Electrical and Computer Engineering, Professor at the Coordinated Science Laboratory, Professor with the Information Trust Institute, and Affiliate Professor at the Department of Mechanical Science and Engineering. He is a Chair Professor and the Chief Scientist of the Center for Intelligent and Networked Systems (CFINS), Tsinghua University. He has spent sabbatical years at Twente University of Technology (the Netherlands; 1978-79), and INRIA (France; 1987-88, 1994-95).

[2014.12.19] Lecture: The key role of automatic control theory in Internet and cognitive machine

Speaker: Weibo Gong

Location: Classroom 6A-116, Sixth Teaching Building of Tsinghua University

Time: 9:50 — 12:15, Dec. 19, 2014 (Friday)

Abstract:

The concept of feedback control is fundamental to many fields. In this talk we discuss two important examples. The first is congestion control for the Internet traffic, where our works in the early 2000 has now been adopted by the cable modem standard DOCSIS 3.1 via the Cisco engineers. There is also an effort on to make it the default AQM on all Internet routers, not just cable modems.

The second, more important for the coming technology revolution, is our newly developed theory of how the mind works. Our algorithms are fundamentally different from the current AI approaches, provide plausible answers for several mysteries of mind, and are feasible for computer implementations.

Biography of Prof. Weibo Gong

Weibo Gong received his Ph.D. in Engineering Sciences from the Division of Applied Sciences at Harvard University in 1987, and since has been with the Department of Electrical and Computer Engineering at University of Massachusetts, Amherst. He is now a full professor of Electrical and Computer Engineering and an adjunct professor of the Department of Computer Science at the same campus. Dr. Gong has received the IEEE Control Systems Society George Axelby outstanding paper award in 1997, University of Massachusetts Amherst Engineering College outstanding senior faculty award in 2002, and the University of Massachusetts Amherst Chancellor's medal in 2009. He is an IEEE Fellow since 1998. Dr. Gong is active in IEEE control systems society. He is the Program Chair for the 2004 IEEE Conference on Decision and Control. Dr. Gong's research interests include network modeling and control, stochastic dynamic systems, communication security, and the foundational algorithms for intelligence.

[2014.06.05] Lecture: Efficient Optimization for a Sustainable Future

Speaker: Bengt Lennartson

Location: Room 407, Main Building of Tsinghua University

Time: 10:00–11:00 a.m., Jun. 5, 2014 (Thursday)

Abstract:

A sustainable future requires economical, human and environmental sustainability. Focusing on automation systems, these three aspects are in this talk illustrated by modeling and optimization of moving and interacting devices. More specifically, novel methods for energy optimization of multi-robot cells are presented. A multi-robot system can be considered as a hybrid system, including continuous movements and high-level discrete interactions. A generic modeling framework for hybrid systems is therefore introduced based on modular predicate transition models. Efficient energy optimization is then obtained, applying suitable abstractions and a recent integrated constraint and nonlinear programming procedure. Robustness issues and online adaption are also incorporated to handle uncertainties in the controlled system. Finally, a flexible event driven data management system is presented, called the “twittering factory”. Traditional database systems are then replaced by massive unstructured data, which is transformed to knowledge utilizing internet search engine techniques. To summarize, the goal of this talk is to present a set of recently proposed generic concepts that support the development of flexible and sustainable automation systems based on the latest modeling and software technology.

Biography of Prof. Bengt Lennartson

Bengt Lennartson received the Ph.D. degree in automatic control from Chalmers University of Technology, Gothenburg, Sweden, in 1986. Since 1999, he has been a Professor of the Chair of Automation, Department of Signals and Systems. He was Dean of Education at Chalmers from 2004 to 2007, and 2015 he will be the General Chair of the 2015 IEEE Conference on Automation Science and Engineering in Gothenburg. His main areas of interest include discrete event and hybrid systems, especially for manufacturing applications, as well as robust feedback control.

[2014.06.03] Lecture: Prevention and Mitigation of Cascading Outages in Smart Power Transmission Grid: New Challenges and Solutions

Speaker: Kai Sun, Assistant Professor

Location: Room 3-620, FIT Building of Tsinghua University

Time: 10:30–11:30, Jun. 3, 2014 (Tuesday)

Abstract:

Since the Northeast Blackout in 1965, US electricity utilities have made many efforts to enhance the reliability of power grids, but cascading outages continued to happen followed by catastrophic blackouts. A power grid blackout is typically the result of a long sequence of disturbances, which begin with initial events, impact network topology, cause oscillations in generators, increase system vulnerabilities, and trigger cascading outages toward grid collapse and instability. At present, the rapid growth of regional electricity markets and the increasing integration of intermittent resources (e.g. renewable generation and demand response) at a time without corresponding growth in transmission infrastructure will stress power grids, bring many uncertainties to grid operations and, as a result, increase the probability of cascading outages. Therefore, it is vitally important to develop online techniques for situational awareness and self-healing protection/control to prevent or mitigate cascading outages against a blackout. Electricity utilities are building synchrophasor-based wide-area measurement systems, which offer GPS-synchronized real-time phasor measurements authentically presenting the dynamics of a power grid. This presentation will talk about how synchrophasors may help prevent and mitigate cascading outages against a blackout. The speaker will share his study results and visions on addressing three critical questions: WHERE and WHEN a power grid may collapse under cascading outages, and WHAT to do to avoid a blackout? A potential technique, intelligent system separation (also called adaptive islanding), will be presented in detail to address the three questions.

Biography of Prof. Kai Sun

Kai Sun is an Assistant Professor in the University of Tennessee, Knoxville (UTK) with the Department of Electrical Engineering and Computer Science, and also a member of the Center for Ultra-Wide-Area-Resilent Electric Energy Transmission Networks (CURENT) headquartered in UTK. Kai Sun received a Bachelor’s Degree in Automation in 1999 and a Ph.D. degree in Control Science and Engineering in 2004 from Tsinghua University in Beijing, China.

Before coming to UTK, Dr. Sun was a Project Manager with the Electric Power Research Institute (EPRI) in Palo Alto, California from 2007 to 2012 for the R&D programs in Grid Operations and Planning and Renewable Integration. Earlier, he worked as a research associate at Arizona State University in Tempe and a postdoctoral fellow at the University of Western Ontario in London, Ontario. His current research activities focus on complex systems, wide-area measurements based power system analysis and control, and application of artificial intelligence in power systems.

news20140603as
news20140603bs

Original Size: [1] [2]

[2014.05.26] Lecture: Stochastic Unit Commitment with Intermittent Distributed Wind Generation

Speaker: Prof. Peter B. Luh

Location: Room 407, Main Building of Tsinghua University

Time: 15:30–17:00, May. 26, 2014 (Monday)

Abstract:

Although the unique characteristics of intermittent wind generation have been acknowledged and drastic impacts of sudden wind drops have been experienced, no effective integration approaches have been developed. In this talk, transmission capacity constraints are first ignored. In this case, aggregated wind generation is modeled as a discrete Markov process with state transition matrices established based on historical data. Wind generation is then integrated into system demand with multiple net demand levels at each hour. To accommodate the uncertain net demand, a stochastic unit commitment problem is formulated based on states instead of scenarios. The objective is to optimize the commitment of conventional generators to minimize the total expected cost while satisfying all possible net demand levels. The advantage of this formulation is that the state at a time instant summarizes the information of all previous instants in a probabilistic sense for reduced complexity. With the objective function and constraints formulated in a linear manner, the problem is effectively solved by using the branch-and-cut method. Numerical testing shows that the new approach is effective and robust through examining cases resembling the sudden wind drop in Texas in February 2008.

When transmission capacity constraints are considered, wind generation at different locations cannot be aggregated and is modeled as a Markov chain per wind node, and the resulting global states are a large number of combinations of nodal states. To avoid explicitly considering all such global states, interval analysis is synergistically integrated with the Markovian approach in this paper. The key is to divide the generation level of a conventional unit into a Markovian component that depends on the local state, and an interval component that manages extreme combinations of non-local states. With appropriate transformations, the problem is converted to a linear form and is solved by using branch-and-cut. Numerical results demonstrate that the over-conservativeness of pure interval optimization is much alleviated, and the new approach is effective in terms of computational efficiency, simulation cost, and solution feasibility.

Biography of Prof. Peter B. Luh

Peter B. Luh received his B.S. from National Taiwan University, M.S. from M.I.T., and Ph.D. from Harvard University. He has been with the University of Connecticut since 1980, and currently is the SNET Professor of Communications & Information Technologies. He was the Head of the Department of Electrical and Computer Engineering from 2006 to 2009. He is also a member of the Chair Professors Group, Center for Intelligent and Networked Systems (CFINS) in the Department of Automation, Tsinghua University, Beijing, China. Professor Luh is a Fellow of IEEE. He was the VP of Publications of RAS (2008-2011), the founding Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering (2003-2007), and the Editor-in-Chief of IEEE Transactions on Robotics and Automation (1999-2003). He received IEEE Robotics and Automation Society 2013 Pioneer Award for his pioneering contributions to the development of near-optimal and efficient planning, scheduling, and coordination methodologies for manufacturing and power systems. His research interests include Smart Power Systems – smart grid, design of auction methods for electricity markets, robust renewable (wind and solar) integration to the grid, and electricity load and price forecasting; Intelligent Manufacturing Systems – planning, scheduling, and coordination of design, manufacturing, and service activities; Smart and Green Buildings and Eco Communities – optimized energy management, HVAC fault detection and diagnosis, emergency crowd guidance, and eco communities.

news20140526_2a
news20140526_2b

Original Size: [1] [2]

[2014.05.26] Lecture: Intelligent Feedback Control for Operation of Complex Industrial Processes

Speaker: Tianyou Chai

Location: Room 511, Main Building of Tsinghua University

Time: 14:00–15:00, May. 26, 2014 (Monday)

Abstract:

Process control should aim at not only ensuring controlled variables to best follow their set points, but also requiring the optimal control for the operation of the whole plant to make the operational indices (e.g. quality, efficiency and consumptions during the production phase) into their targeted ranges. It also requires that operational indices for quality and efficiency should be enhanced as high as possible, whilst the indices related to consumptions are kept at their lowest possible level. Based upon a survey on the existing operational optimization and control methodologies, this talk presents a data-driven hybrid intelligent feedback control for operation of complex industrial processes and a hybrid simulation system.

Simulations and industrial applications to a roasting process for the hematite ore mineral processing industry are used to demonstrate the effectiveness of the proposed method. Issues for future research on the optimal operational control for complex industrial processes are outlined in the final section.

Biography of Tianyou Chai

Tianyou Chai received the Ph.D. degree in control theory and engineering in 1985 from Northeastern University, Shenyang, China, where he became a Professor in 1988. He is the founder and Director of the Center of Automation, which became a National Engineering and Technology Research Center and a State Key Laboratory. He is a member of Chinese Academy of Engineering, IFAC Fellow and IEEE Fellow, director of Department of Information Science of National Natural Science Foundation of China.

His current research interests include modeling, control, optimization and integrated automation of complex industrial processes. He has published 150 peer reviewed international journal papers. His paper titled Hybrid intelligent control for optimal operation of shaft furnace roasting process was selected as one of three best papers for the Control Engineering Practice Paper Prize for 2011-2013. He has developed control technologies with applications to various industrial processes. For his contributions, he has won 4 prestigious awards of National Science and Technology Progress and National Technological Innovation, the 2007 Industry Award for Excellence in Transitional Control Research from IEEE Multiple-conference on Systems and Control.

news20140526
news20140526_b

Original Size: [1] [2]

[2014.05.21] Lecture: A Synergistic Combination of Surrogate Lagrangian Relaxation and Branch-and-Cut for MIP Problems in Power Systems

Speaker: Prof. Peter B. Luh

Location: Room N226, South Building of Mathematics Institute, Chinese Academy of Sciences

Time: 10:00 – 11:00 a.m., May. 21, 2014 (Wednesday)

Abstract:

Mixed-integer programming problems are prevalent in power systems. Historically, Lagrangian relaxation and subgradient methods were used to solve such problems by exploiting separability through relaxing coupling constraints and decomposing relaxed problems into subproblems. Although subgradient methods have been widely used to update multipliers, they require the relaxed problem to be fully optimized, and this can be computationally expensive. Moreover, convergence can be slow because multipliers often zigzag across “ridges” of the dual function. The recent trend is to solve these problems by using the branch-and-cut method that exploits problem linearity. However, complex problems such as stochastic unit commitment or even the deterministic version with combined cycle units can pose major computational challenges. The reason is that cuts that define a convex hull, referred to as “facet-defining” or “strong” cuts, are problem-dependent and may be difficult to obtain. Complex transitions among combined cycle states associated with one unit, for example, are treated as global constraints, and affect the entire problem. Very recently, we developed the Surrogate Lagrangian Relaxation method where a proper direction to update multipliers can be obtained without optimally solving all subproblems with much reduced computational effort and zigzagging. More importantly, convergence to the optimum does not require the knowledge of the optimal dual value. This was achieved with a constructive process in which distances between Lagrange multipliers at consecutive iterations decrease, and as a result, multipliers converge to a unique limit. The decrease cannot be too large to avoid premature termination of the iterative updating process. To enable an efficient exploitation of separability as well as linearity, surrogate Lagrangian relaxation and branch-and-cut are synergistically combined where surrogate Lagrangian relaxation is used to decompose a problem into subproblems by relaxing coupling constraints, and each subproblem is solved by using branch-and-cut. After decomposition, constraints associated with a subproblem are handled locally and no longer affect the entire problem. Furthermore, effective cuts for individual subproblems can be obtained easier than for the original problem. Numerical results on unit commitment with combined cycles demonstrated that the new approach is computationally efficient. The approach thus laid the foundation and opens up a new direction for optimizing MIP problems in power systems and beyond.

Biography of Prof. Peter B. Luh

Peter B. Luh received his B.S. from National Taiwan University, M.S. from M.I.T., and Ph.D. from Harvard University. He has been with the University of Connecticut since 1980, and currently is the SNET Professor of Communications & Information Technologies. He was the Head of the Department of Electrical and Computer Engineering from 2006 to 2009. He is also a member of the Chair Professors Group, Center for Intelligent and Networked Systems (CFINS) in the Department of Automation, Tsinghua University, Beijing, China. Professor Luh is a Fellow of IEEE. He was the VP of Publications of RAS (2008-2011), the founding Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering (2003-2007), and the Editor-in-Chief of IEEE Transactions on Robotics and Automation (1999-2003). He received IEEE Robotics and Automation Society 2013 Pioneer Award for his pioneering contributions to the development of near-optimal and efficient planning, scheduling, and coordination methodologies for manufacturing and power systems. His research interests include Smart Power Systems – smart grid, design of auction methods for electricity markets, robust renewable (wind and solar) integration to the grid, and electricity load and price forecasting; Intelligent Manufacturing Systems – planning, scheduling, and coordination of design, manufacturing, and service activities; Smart and Green Buildings and Eco Communities – optimized energy management, HVAC fault detection and diagnosis, emergency crowd guidance, and eco communities.

[2014.04.21] Lecture: Conflict resolution using graphs with applications in wireless networks and protein docking

Speaker: Prof. Yannis Paschalidis

Location: Room 707, Main Building

Time: 10:30 – 11:30 a.m., Apr. 21, 2014 (Monday)

Host: Qianchuan Zhao

Abstract:

We consider graphs with nodes representing decisions and edges representing conflicts among two decisions. Nodes are further assigned weights indicating the reward of the corresponding decision. In such a graph, the Maximum Weighted Independent Set (MWIS) problem is to select a set of nodes, no two of which are adjacent, with the largest possible total weight. This is equivalent to selecting a "conflict-free" set of decisions with maximal reward. MWIS is NP-hard. I will present a new fully distributed algorithm consisting of two phases, each of which requires only local information and is based on message passing between nodes of the graph. The first phase solves a relaxation of MWIS, and the second phase constructs a feasible solution using a deterministic estimation algorithm. We show that our algorithm always outputs an optimal solution to MWIS for perfect graphs. I will illustrate the efficacy of the new algorithm in two very different applications domains: scheduling in wireless networks and protein docking.

Biography of Prof. Yannis Paschalidis

Yannis Paschalidis is a Professor and Distinguished Faculty Fellow of Electrical and Computer Engineering, Systems Engineering, and Biomedical Engineering at Boston University. He is the Director of the Center for Information and Systems Engineering (CISE). He obtained a Diploma (1991) from the National Technical University of Athens, and an M.S. (1993) and a Ph.D. (1996) from the Massachusetts Institute of Technology (MIT), all in Electrical Engineering and Computer Science. He has been at Boston University since 1996. His current research interests lie in the fields systems and control, networking, applied probability, optimization, operations research, computational biology, medical informatics, and bioinformatics.

Prof. Paschalidis' work on communication and sensor networks has been recognized with a CAREER award (2000) from the National Science Foundation, the second prize in the 1997 George E. Nicholson paper competition by INFORMS, and the best student paper award at the 9th Intl. Symposium of Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt 2011) won by one of his Ph.D. students for a joint paper. His work on protein docking (with his collaborators) has been recognized for best performance in modeling selected protein-protein complexes against 64 other predictor groups (2009 Protein Interaction Evaluation Meeting). He was an invited participant at the 2002 Frontiers of Engineering Symposium organized by the US National Academy of Engineering. Prof. Paschalidis is a Fellow of the IEEE and the Editor-in-Chief of the IEEE Transactions on Control of Network Systems.

news20140421
news20130905

Original Size: [1] [2]

[2014.03.31] Lecture: Computational game theory applied to electricity market-games played with heterogeneous beliefs

Speaker: Dr. Qiu Zhifeng

Location: Room 407, Main Building

Time: 14:00 – 16:00, Mar. 31, 2014 (Monday)

Host: Qingshan Jia

Abstract:

In the context of liberalized markets, market outcomes generally result from the strategic interactions of all market players. Generation company (Genco), as the distributed players, build their subjective demand evaluations (SDFs) about market for optimal bidding purpose. The picture of a real electricity market game in Genco’s eye is ‘playing is believing’. Therefore, a question naturally comes to the table: how those SDFs with the heterogeneous manner impact individual player’s decision and game results. To answer this question, this presentation relaxes a conventional assumption, commonly used in the classical oligopolistic equilibrium model, that a correct and uniform demand knowledge is shared by all Gencos. The investigations are carried out from three perspectives:Firstly, the impact of SDFs is analyzed in a dynamic Cournot game and a transmission constrained supply function bidding market game respectively. The economic value of perfect information in the two game settings is discussed. Secondly, to alleviate the system oscillations caused by SDFs in the conventional conjectural variation (CV)-based learning bidding method, a data filter is designed to make bidding system stable. Finally, the stochastic learning technique, i.e. agent-based reinforcement learning, is employed to answer the research questions from another point of view. The comparisons are made between the equilibrium-oriented (EO) approach mentioned above and the multi-agent learning (MAL) approach.

The findings from this presentation provide insights on several interesting issues aroused by assuming players’ heterogeneous beliefs in computational game theory under the background of electricity market. The results can provide important guidelines in multiple perspectives, e.g. the effective design of a dynamic bidding learning process considering players’ heterogeneous demand knowledge; the policy implications of certain bidding behaviors caused by the imperfect demand evaluations, etc.

Biography of Dr. Qiu Zhifeng

Dr. Qiu Zhifeng received his Ph.D degree in Katholieke Universiteit Leuven (KUL). Post-doctorial fellow, ELECTA/ESAT, Katholieke Universiteit Leuven. B.E., Central South University (CSU), 2001. M.E., Central South University (CSU), 2004. He have been working on power system optimization and scheduling problems and modeling problems. His research interests are mainly in computational game theory’s applications in electricity market; machine learning of multi-agents in dynamic complex system; modeling, controlling and optimization of complex industrial system.

[2013.12.27] Lecture: Consensus based approaches for distributed estimation

Speaker: Prof. Alessandro Giua

Location: Room 407, Main Building

Time: 10:00-11:00 a.m., 2013-12-27 (Friday)

Host: Qingshan Jia

Abstract:

The objective of this talk is twofold. In a first part of the talk, the classical notion of consensus for a multi-agent system will be reviewed. In the second part, a new approach for the estimation of network parameters of interest based on consensus algorithms will be presented.

The problem of consensus, i.e., driving the state of systems interacting in a network to a common value, has many interesting applications and has recently received much attention within the control community. Consensus is reached through a local interaction rule between the interconnected systems that can take many forms. Two main interactions rules are discussed: the first is the standard synchronous consensus rule, where all agents update their state at the same time: the second is an asynchronous consensus rules called gossip.

The emerging behavior of a multi-agent system is strictly related to the topology of the underlying network, which in turn is related to the spectrum of the Laplacian matrix of the network graph. In the last part of the talk a decentralized algorithm to estimate the Laplacian eigenvalues is presented. The basic idea is to provide a local interaction rule among agents so that their state trajectory is a linear combination of sinusoids oscillating only at frequencies function of the eigenvalues of the Laplacian matrix. In this way, the problem of decentralized estimation of the eigenvalues is mapped into a standard signal processing problem in which the unknowns are the finite number of frequencies at which the signal oscillates.

Biography of Prof. Alessandro Giua

Alessandro Giua is professor of Automatic Control at the Department of Electrical and Electronic Engineering of the University of Cagliari, Italy and at the Laboratory of Information and Systems Sciences of Aix-Marseille University, France. He received a Ph.D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, Troy, New York in 1992. His research interests include discrete event systems, hybrid systems, networked control systems, Petri nets, failure diagnosis. On these topics he has published over 200 papers, two textbooks and has managed several research projects. He is the main editor of the journal Nonlinear Analysis: Hybrid Systems, and is or has been a member of the editorial board of the journals: IEEE Trans. on Automatic Control; IEEE Trans. on Control Systems Technology; IEEE Trans. on Industrial Informatics; Discrete Event Dynamic Systems; European Journal of Control. He is a member of the Board of Governors of the IEEE Control Systems Society for 2013-2015, chair of the IFAC Technical Committee 1.3 on Discrete Event and Hybrid Systems, and a member of the Steering Committees of the conference series IEEE CASE and IFAC ADHS.

[2013.11.25] Lecture: Secure Estimation and Control in Cyber-Physical Systems

Speaker: Yilin Mo

Location: Room 407, Main Building

Time: 10:00-11:30 a.m., 2013-11-25 (Monday)

Host: Qingshan Jia

Abstract:

The concept of Cyber-Physical System (CPS) refers to the embedding of sensing, communication, control and computation into the physical spaces. Today, CPSs can be found in areas as diverse as aerospace, automotive, chemical process control, civil infrastructure, energy, health-care, manufacturing and transportation, most of which are safety critical. Any successful attack to such kind of systems can cause major disruptions, leading to great economic losses and may even endanger human lives. The first-ever CPS malware (called Stuxnet) was found in July 2010 and has raised significant concerns about CPS security. The tight coupling between information and communication technologies and physical systems in CPS introduces new security concerns, requiring a rethinking and reexamining of the commonly used objectives and methods. In this talk, we provide two different cyber-physical threat models of CPS and analyze the performance of CPS under malicious attacks. We also develop new secure and resilient estimation and control algorithms to counter the attack.

Biography of Yilin Mo

Yilin Mo is a postdoctoral researcher in the Department of Control and Dynamical Systems at California Institute of Technology. He received his Ph.D. In Electrical and Computer Engineering from Carnegie Mellon University in 2012 and his Bachelor of Engineering degree from Department of Automation, Tsinghua University in 2007. His research interests include secure control systems and networked control systems, with applications in sensor networks.

[2013.10.08] Lecture: Adaptive and responsive built environments

Speaker: Burcin Becerik-Gerber

Location: Room 407, Main Building

Time: 10:00-11:30 a.m., 2013-10-08 (Tuesday)

Host: Qingshan Jia

Abstract:

In the U.S., buildings consume 48% of energy, half of which is consumed by commercial buildings. Energy use in commercial buildings depends on the collective decisions of many individuals in different sorts of roles, including building operators and ordinary occupants, who lack direct financial incentives. Making significant progress towards sustainable building energy usage requires a broad shift in how commercial buildings are used and operated. iLAB research aims at building interactive and intelligent environments with the end goal of impacting both human and building behavior to fulfill the goal of reduced energy use, and increased comfort in buildings. We investigate novel approaches to have environments that are not only aware of and make use of their userslocations, processes, activities or preferences but also create environments that learn and predict what is going to happen in the foreseeable future. The focus is on establishing human centered-environments that communicate directly with the users in a dynamic and informal way, and deliver context aware, personalized and timely information for supporting decision-making, collaborative problem solving, management of resources and learning. The research investigates how to adapt to the needs of different types of users (e.g., facility managers, first responders) through the use of adjustable autonomy, automation and collaboration. The lecture will focus on iLAB current research in human-building interaction.

Biography of Burcin Becerik-Gerber

Dr. Becerik-Gerber research focuses on the automation of collection and analysis of the data needed for complex built environments, and formalization of systematic processes for data representation and visualization to improve built-environment efficiency, sustainability, and maintainability. Dr. Becerik-Gerber holds degrees in both Civil and Environmental Engineering and Architecture. Burcin graduated from Istanbul Technical University with a Bachelor of Architecture (1999) and an M.S. in Architecture (2001). She attended the University of California at Berkeley, where she received an M.S. in Civil and Environmental Engineering (2002). She earned her Doctor of Design (2006) degree from Harvard University in the field of Project Management and Information Systems. After graduating from Harvard University, she worked as a consultant and taught in the area of information automation and management for three years. In 2008, she joined the Sonny Astani Department of Civil and Environmental Engineering at the University of Southern California as an Assistant Professor. She has 30 peer-reviewed journal papers and over 40 published peer-reviewed conference papers. Her work has received support worth over $4.4m from a variety of sources, including National Science Foundation, Department of Energy and Department of Transportation. MIT Technology Review has recently named her as one of the world top young innovators under the age of 35. She has been selected to take part in the National Academy of Engineering's Frontiers of Engineering Education Symposium in 2011 and Frontiers in Engineering Symposium in 2013 for her innovative research and educational approaches in civil engineering. She is currently the director of the Innovation in Integrated Informatics LAB, http://i-lab.usc.edu/. She is advising nine Ph.D. students, three M.S. students and five undergraduate students in the nformatics For Intelligent Built Environmentsfocus area (http://cee.usc.edu/admission/phd-programs/informatics-for-intelligent-built-environments.htm). She also serves as an Associate Editor for ASCE Journal of Computing in Civil Engineering.

[2013.09.26] Lecture: Computable analysis and control synthesis over complex dynamical systems via formal verification

Speaker: Alessandro Abate

Location: Room 3-620, FIT Building

Time: 4:30-5:30 p.m., 2013-09-26 (Thursday)

Host: Qianchuan Zhao, 62783612, zhaoqc@tsinghua.edu.cn

Abstract:

This talk looks at the development of abstraction techniques based on formal approximation schemes to investigate the dynamics of complex systems and to provide computable approaches for the synthesis of control architectures. The talk in particular zooms in on two different classes of models to elucidate the approach: the first deals with stochastic hybrid systems, a class of probabilistic models with heterogeneous dynamics, whereas the second focuses on max-plus linear models, which are discrete-event systems employed for scheduling and synchronization. Case studies from energy systems and railway networks will be employed to elucidate the concepts.

Biography of Alessandro Abate

Alessandro Abate is a University Lecturer in the Department of Computer Science at the University of Oxford. He received a Laurea degree in Electrical Engineering (summa cum laude) in October 2002 from the University of Padova. As an undergraduate he also studied at UC Berkeley and RWTH Aachen. He earned an MS in May 2004 and a PhD in December 2007, both in Electrical Engineering and Computer Sciences, at UC Berkeley, working on Systems and Control Theory with S. Sastry. Meanwhile he was an International Fellow in the CS Lab at SRI International in Menlo Park (CA). Thereafter, he has been a PostDoctoral Researcher at Stanford University, in the Department of Aeronautics and Astronautics, working with C. Tomlin on Systems Biology in affiliation with the Stanford School of Medicine. From June 2009 to mid 2013 he has been an Assistant Professor at the Delft Center for Systems and Control, TU Delft - Delft University of Technology, working with his research group on Verification and Synthesis over complex systems and on Systems Biology.

[2013.09.05] Lecture: Optimal pricing of services on social network with stochastic optimization

Speaker: Prof. Alexei A. Gaivoronski

Location: Room 3-620, FIT Building

Time: 10:30-11:30 a.m., 2013-09-05 (Thursday)

Host: Qianchuan Zhao, 62783612, zhaoqc@tsinghua.edu.cn

Abstract:

This paper develops a combined simulation and optimization model that allows to optimize different service pricing strategies defined on the social networks under uncertainty. For a specific reference problem we consider a telecom service provider whose customers are connected in such network. Besides the service price, the acceptance of this service by a given customer depends on the popularity of this service among the customer's neighbors in the network. One strategy that the service provider can pursue in this situation is to stimulate the demand by offering the price incentives to the most connected customers whose opinion can influence many other participants in the social network.

We develop a simulation model of such social network and show how this model can be integrated with stochastic optimization in order to obtain the optimal pricing strategy. Our results show that the differentiated pricing strategies can increase substantially the revenue of service provider operating on a social network.

Biography of Alexei A. Gaivoronski

Dr. Alexei A. Gaivoronski is Professor of Industrial Economics and Operations Research at the Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology (NTNU).He got his PhD in operations research from Moscow Institute for Physics and Technology. His research interests include information and telecommunications (ICT) economics, optimization under uncertainty,simulation and analysis of stochastic systems, risk management in finance, industry and services. He has published more than 70 research papers on these subjects. He hold different teaching and research positions at International Institute for Applied Systems Analysis (Austria), V. Glushkov Institute of Cybernetics (Ukraine), Universities of Milan and Caglilari (Italy), University of Paris Sud (France).Besides academia, he worked and consulted for different enterprises in ICT sector (Italtel, IBM, Xerox, Telenor).

news20130905
news20130905

Original Size: [1] [2]

[2013.09.02] Lecture: History of Systems Control (1959-2013) via Personal Anecdotes

Speaker: Prof. Yu-Chi Ho

Location: Lecture Hall, FIT Building

Time: 10:30-11:30 a.m., 2013-09-02 (Monday)

Host: Qianchuan Zhao, 62783612, zhaoqc@tsinghua.edu.cn

Abstract:

In the spirit of the documentary film "History of the World in 2 hours (from the Big Bang to the 21st Century") and the 2007 book "History of the World via 100 Objects (from the Stone age to the Modern world)" The speaker proposes to deliver an account of this modern era of Systems and Control using his own anecdotal personal experiences living through this period from the Kalman Filter to the age of Automation and "Big Data" illustrating the developments.

1. Kalman Filter

2. The Witsenhausen Problem and Decentralized Control

3. Manufacturing Automation

4. Simulation and Modeling

Biography of Prof. Yu-Chi Ho

Prof. Yu-Chi Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard faculty. Since 1969 he has been Gordon McKay Professor of Engineering and AppliedMathematics. In 1988, he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Professor of Systems Engineering at Harvard and as visiting professor to the Cockrell Family Regent's Chair in Engineering at the University of Texas, Austin. In 2001, he retired from teaching duties at Harvard and became a Research Professor (2001-2006) and also was appointed to be a chair professor and chief scientist (part time), at the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing China.

20130902as
20130902bs

Original Size: [1] [2]

[2013.08.27] Lecture: Local properties of behavioral analysis in finance

Speaker: Prof. Xi-Ren Cao

Location: Room 1-315, FIT Building

Time: 10:30-11:30 a.m., 2013-08-27 (Tuesday)

Host: Qianchuan Zhao, 62783612, zhaoqc@tsinghua.edu.cn

Abstract:

In finance, it has been long realized that the expected utility theory cannot explain many ``irrational behavior," which is nonlinear in nature. Theories and methodologies have been developed for characterizing such non-linear behavior and dealing with portfolio optimization problem with the non-linear criteria. Among them are Yaari's axiomatic approach, Quiggin's rank-dependent expected utility, Machina's smoothness analysis, and Zhou's quantile approach to portfolio selection. We take a different perspective; the nonlinear nature makes sensitivity analysis, in particular, perturbation analysis, a suitable tool in exploring the nature of the problem. Our recent research explores the local properties in non-linear behavior analysis and their relations to the global ones.

One important property we discovered is the so called mono-linearity, which says that Yaari's representation in fact maintains some local linearity. With the mono-linearity, We proceed in three directions. 1. Just like in perturbation analysis, the mono-linearity allows use sample path based derivatives as the unbiased estimate of the performance gradient; therefore, we develop algorithms for performance optimization in portfolio management and develop theory for it. The results are consistent with those with Zhou; and the method can also be applied to new problems. 2. The mono-linearity explains, in one angle, why Yaari's theory cannot explain some paradoxes, and we developed new axioms to extend Yaari's axiomatic approach; in particular, we proved that the famous independent axiom can be replaced by a local linear axiom, and thus simplified the theory. 3. bvWe study other non-liner behavior when the mono-linearity does not hold; e.g., the theory with disappointment and more.

Biography of Prof. Xi-Ren Cao

Xi-Ren Cao is a chair professor of Shanghai Jiao Tong University and an affiliate member of the Institute for Advanced Study at the Hong Kong University of Science and Technology (HKUST). He has worked as a consulting engineer for Digital Equipment Corporation, a research fellow at Harvard University, and a reader, professor, and chair professor at HKUST. He owns three patents in data- and tele- communications and has published three books in the areas of performance optimization and discrete event dynamic systems. Selected honors include being Fellow of IEEE and IFAC and best paper awards from the IEEE Control Systems Society and the Institution of Management Science. He has served as the Editor-in-Chief of Discrete Event Dynamic Systems: Theory and Applications, as an Associate Editor at Large of the IEEE Transactions of Automatic Control, as a Member of the Board of Governors of the IEEE Control Systems Society, and as a Member on the Technical Board of IFAC. His current research areas include financial engineering, stochastic learning and optimization, performance analysis of economic systems, and discrete event dynamic systems. He holds a Ph.D degree from Harvard University.

Prof. Xi-Ren Cao
Prof. Xi-Ren Cao

Original Size: [1] [2]

[2013.05.31] Lecture: Information Relaxation and Duality in Stochastic Optimal Control

Speaker: Dr. Enlu Zhou (Assistant Professor of University of Illinois Urbana-Champaign)

Location: Room 407, Central Main Building

Time: 10:00-11:30 a.m., 2013-05-31 (Friday)

Host: Li Xia, Department of Automation, Tsinghua

Abstract:

In this talk, I will talk about some recent research development in the approach of information relaxation to explore duality in Markov decision processes and controlled Markov diffusions. The main idea of information relaxation is to relax the constraint that the decisions should be made based on the current information and impose a penalty to punish the access to the information in advance. The weak duality, strong duality and complementary slackness results are then established, and the structures of optimal penalties are revealed. The dual formulation is essentially a sample path-wise optimization problem, which is amenable to Monte Carlo simulation. The duality gap associated with a sub-optimal policy/solution also gives a practical indication of the quality of the policy/solution.

Biography of Dr. Enlu Zhou

Dr. Enlu Zhou received the B.S. degree with highest honors in electrical engineering from Zhejiang University, China, in 2004, and the Ph.D. degree in electrical engineering from the University of Maryland, College Park, in 2009. Since then she has been an Assistant Professor at the Industrial & Enterprise Systems Engineering Department at the University of Illinois Urbana-Champaign. Her research interests include simulation optimization, Markov decision processes, and Monte Carlo statistical methods. She is a recipient of the "Best Theoretical Paper" award at the 2009 Winter Simulation Conference and the 2012 AFOSR Young Investigator award.

[2013.05.28] Lecture: Smart Buildings

Speaker: Prof. Peter B. Luh

Location: Room 511, Central Main Building

Time: 10:00-11:30 a.m., 2013-05-28 (Tuesday)

Host: Qianchuan Zhao, Department of Automation, Tsinghua

Abstract:

Considering that energy use in buildings represents more than 40% of global energy consumption and that humans spend 90% of the time indoors, technologies enabling smarter buildings can lead to significant reductions in greenhouse gas emissions, and produce a comfortable, efficient, and safe environment. This is to be achieved through smart sensing, advanced automation, and intelligent computing/communication technologies to efficiently operate, monitor, and maintain buildings.

In this talk, three selected topics will be highlighted, including 1) Integrated Building Energy Management, 2) HVAC (Heating, Ventilation, and Air Condition) Fault Detection, and 3) Crowd Guidance in Building Emergencies. For each topic, problem importance, challenges in problem formulation and solution methodology as well as our novel ideas will be stressed. The goal is to demonstrate that Smart Buildings are a fertile problem context for meaningful research and development. The talk will end with a brief introduction of the Technical Committee on Smart Buildings of the IEEE Robotics and Automation Society (RAS).

Biography of Prof. Peter B. Luh

Peter B. Luh received his B.S. from National Taiwan University, M.S. from M.I.T., and Ph.D. from Harvard University. He has been with the University of Connecticut since 1980, and currently is the SNET Professor of Communications & Information Technologies. He was the Head of the Department of Electrical and Computer Engineering from 2006 to 2009. He is also a member of the Chair Professors Group, Center for Intelligent and Networked Systems (CFINS) in the Department of Automation, Tsinghua University, Beijing, China. Professor Luh is a Fellow of IEEE. He was the VP of Publications of RAS (2008-2011), the founding Editor-in-Chief of the IEEE Transactions on Automation Science and Engineering (2003-2007), and the Editor-in-Chief of IEEE Transactions on Robotics and Automation (1999-2003). His interests include Smart Power Systems smart grid, design of auction methods for electricity markets, robust renewable (wind and solar) integration to the grid, and electricity load and price forecasting with demand response; Intelligent Manufacturing Systems planning, scheduling, and coordination of design, manufacturing, and service activities; Smart and Green Buildings and Eco Communities optimized energy management, HVAC fault detection and diagnosis, emergency crowd guidance, and eco communities.

[2013.04.17] Lecture: The geometry of (thin) SVD revisited for large-scale computations

Speaker: Prof. Rodolphe Sepulchre, University of Liege, Belgium

Location: Room 511, Central Main Building

Time: 10:00-11:00 a.m., 2013-04-17 (Wednesday)

Host: Li Xia, Department of Automation, Tsinghua

Abstract:

The talk will introduce a Riemannian framework for large-scale computations over the set of low-rank matrices. The foundation is geometric and the motivation is algorithmic, with a bias towards efficient computations in large-scale problems. We will explore how classical matrix factorizations connect the Riemannian geometry of the set of fixed-rank matrices to two well-studied manifolds: the Grassmann manifold of linear subspaces and the cone of positive definite matrices. The theory will be illustrated on various applications, including low-rank Kalman filtering, linear regression with low-rank priors, matrix completion, and the choice of a suitable metric for Diffusion Tensor Imaging.

Biography of Prof. Rodolphe Sepulchre

Rodolphe Sepulchre received the engineering degree (1990) and the PhD degree (1994), both in mathematical engineering, from the Université catholique de Louvain, Belgium. He was a BAEF fellow in 1994 and held a postdoctoral position at the University of California, Santa Barbara from 1994 to 1996. He was a research associate of the FNRS at the Université catholique de Louvain from 1995 to 1997. He moved in 1997 to the Université de Liège, where he is currently professor in the department of Electrical Engineering and Computer Science. He was department chair from 2009 to 2011. He held a visiting position at Princeton University in 2002-2003 and at the Ecole des Mines de Paris in 2009-2010. Since October 2012, he holds a part-time position at INRIA Lille Europe as the director of the orchestron project.

His current research interests are in control and coordination problems on nonlinear spaces, optimization on manifolds, analysis and synthesis of networks of oscillators and rhythmic systems. He co-authored the monographs "Constructive Nonlinear Control" (Springer-Verla, 1997) and "Optimization on Matrix Manifolds" (Princeton University Press, 2008). He is currently Editor-in-Chief of Systems and Control Letters and an Associate Editor for SIAM Journal of Control and Optimization, the Journal of Nonlinear Science, and Mathematics for Control, Signals, and Systems. In 2008, he was awarded the IEEE Control Systems Society Antonio Ruberti Young Researcher Prize. He is an IEEE fellow and an IEEE CSS distinguished lecturer since 2010.

Prof. Rodolphe Sepulchre give a talk

Original Size: [1]

[2013.01.15] Lecture: Optimal and Robust Scheduling for Networked Control Systems

Location: Room 407, Main Building

Time: 10:00AM, Jan. 15, 2013 (Tuesday)

Abstract:

Networked Control Systems (NCS) enable the integration of an increasing number of complex control systems implemented on distributed control units. The problem is increased as nowadays the manufacturers tend to produce their own control algorithms which need to be integrated into existing NCSs.

This talk discusses theoretical analysis approaches for the properties of NCSs from the control aspect but taking into consideration the issues related to the practical implementation. The aim is to contribute to the bridging of the gap between control theory and computer science since we believe that, if the bandwidth constraints of the communication medium are considered at the controller design stage, the performance of the controller significantly improves. The tools are applicable to time-triggered communication problems in industry, e.g. integration of control systems across automotive control networks, e.g. Flexray, or aerospace systems, e.g. AFDX.

The talk will at first explain NCS tools in the context of linear robust control theory and NCS tools which are then extended to the context of nonlinear plant and control systems.

The results of this work are to be published in the book on "Optimal and Robust Scheduling for Networked Control Systems" by Stefano Longo (University of Cranfield), Tingli Su (BIT), Guido Herrmann and Phil Barber (Jaguar and LandRover) (March 20, 2013).

Biography of Dr Guido Herrmann

Dr Guido Herrmann received the German degree "Diplom-Ingenieur der Elektrotechnik" (with highest honours) from the Technische Universit?t zu Berlin, Germany, and the Ph.D. degree from the University of Leicester, UK, in 1997 and 2001, respectively. From 2001 to 2003, he was a Senior Research Fellow at the Data Storage Institute in Singapore. From 2003 until 2005, he was a Research Associate, Fellow, and Lecturer at the University of Leicester. He joined the University of Bristol, Bristol, UK, as a Lecturer in March 2007, and was a Senior Lecturer from August 2009 until August 2012. In August 2012, he was promoted to the position of a Reader in Control and Dynamics (Associate Professor). He was at several occasions invited to visit Universities and research institutes in the USA, China, Malaysia and Singapore to work with academics such as Professors Frank L Lewis and Sam S Ge. His research considers the development and application of novel, robust and nonlinear control systems. He published more than 120 papers. He is editor of one book and author of one book on "Optimal and Robust Scheduling for Networked Control Systems" (Mar 20, 2013). Dr Herrmann PhD-student Dr S Stefano Longo, first author of the latter book, received the IET 2011 Control PhD Award for his work in the area of networked control systems. Dr Herrmann was main advisor of four Doctorate Degree holders and co-advisor of another four Doctorate Degree holders. His research portfolio as principal investigator amounts to ?747,000 (?3,272,200 as co-investigator). He is a Senior Member of the IEEE, a Technical Editor of the IEEE/ASME Transactions on Mechatronics and an Associate Editor of the International Journal on Social Robotics. He is leading the Nonlinear Robotics Control Group (NRCG) at the Bristol Robotics Laboratory.

Dr Guido Herrmann gave a talk

Original Size: [1]

[2012.12.04] Lecture: Distributed Control of Networked Multi-agent Systems: Algorithms and Applications, Wei Ren, University of California

Location: RM. 3-620 FIT Building

Abstract:

While autonomous agents that perform solo missions can yield significant benefits, greater efficiency and operational capability will be realized from teams of autonomous agents operating in a coordinated fashion. Potential applications for networked multiple autonomous agents include environmental monitoring, search and rescue, space-based interferometers, hazardous material handling, and combat, surveillance, and reconnaissance systems. Networked multi-agent systems place high demands on features such as low cost, high adaptivity and scalability, increased flexibility, great robustness, and easy maintenance. To meet these demands, the current trend is to design distributed control algorithms that rely on only local interaction to achieve global group behavior.

The purpose of this talk is to overview our recent research in distributed control of networked multi-agent systems. Theoretical results on distributed leaderless consensus with vehicle dynamics including first- and second-order linear dynamics, rigid body attitude dynamics, and Euler-Lagrange dynamics, distributed single-leader collective tracking with reduced interaction and partial measurements, distributed multi-leader containment control with local interaction, distributed average tracking with multiple time-varying reference signals, and distributed optimization with non-identical constraints will be introduced. Application examples in multi-vehicle cooperative control including rendezvous, formation keeping, and cooperative herding for wheeled mobile robots, UAV formation flying, deep space spacecraft attitude alignment, and synchronization of networked robotic arms will also be introduced.

Biography of Prof. Wei Ren

Wei Ren received his Ph.D. degree in electrical engineering from Brigham Young University, Provo, UT, in 2004. From October 2004 to July 2005, he was a Postdoctoral Research Associate with the Department of Aerospace Engineering, University of Maryland, College Park, MD. He was an assistant professor (August 2005 to June 2010) and an associate professor (July 2010 to June 2011) with the Department of Electrical and Computer Engineering, Utah State University, Logan. Since July 2011, he has been with the Department of Electrical Engineering, University of California, Riverside, where he is currently an Associate Professor. His research focuses on distributed control of multi-agent systems and autonomous control of unmanned vehicles. He is an author of two books Distributed Coordination of Multi-agent Networks (Springer-Verlag, 2011) and Distributed Consensus in Multi-vehicle Cooperative Control (Springer-Verlag, 2008). Dr. Ren was the recipient of a National Science Foundation CAREER award in 2008. He is currently an Associate Editor for Automatica and Systems and Control Letters.

Prof. Wei Ren
Prof. Wei Ren

Original Size: [1] [2]

[2012.05.30] Lecture: Control of Wind Turbines: Accomplishments and Challenges, Lucy Pao, University of Colorado

Time: 10:00-12:00a.m., March 28th, Mon.

Location: RM. 511 Main Building

Abstract:

Wind energy is recognized worldwide as cost-effective and environmentally friendly and is among the world's fastest-growing electrical energy sources. In particular, China has excellent wind resources, and the development of wind energy in China over the last decade has been phenomenal, with China now the largest wind energy provider worldwide. Despite the amazing growth in the installed capacity of wind turbines in recent years, engineering and science challenges still exist. These large, flexible structures operate in uncertain, time-varying wind and weather conditions and lend themselves nicely to advanced control solutions. Advanced controllers can help achieve the overall goal of decreasing the cost of wind energy by increasing the efficiency, and thus the energy capture, or by reducing structural loading and increasing the lifetimes of the components and turbine structures.

In this talk, we will first provide an overview of wind energy systems. We will describe the main components of wind turbines, the sensors and actuators, the different operating regions, and we will outline the current state of the art in wind turbine modeling and control. We will then discuss our recent work in developing combined feedforward and feedback controllers for wind turbines using novel wind inflow sensing technologies. Model-inverse based controllers, H-infinity controllers, and model predictive controllers can be designed to take advantage of preview wind measurements to yield significant reductions in structural loading while maintaining the power capture levels of the wind turbine. We shall close by discussing a number of challenges and highlighting areas of future work, including coordinated control of arrays of turbines on wind farms and modeling and control of floating offshore wind turbines.

Biography of Prof. Lucy Pao

Lucy Pao received the B.S., M.S., and Ph.D. degrees in Electrical Engineering from Stanford University. She has been a Visiting Scholar at Harvard University, a Visiting Miller Professor at the University of California at Berkeley, and a Visiting Scholar at the US National Renewable Energy Laboratory. She has interests in the areas of control systems (with applications to flexible structures, atomic force microscopes, disk drives, tape systems, power converters, and wind turbines), multisensor data fusion (with applications to unmanned autonomous vehicles, satellites, and automotive active safety systems), and haptic and multimodal visual/ haptic/ audio interfaces (with applications to scientific visualization and spatial communication).

Professor Pao has received a number of awards and has been active in many professional society committees and positions. Selected honors include a US NSF CAREER Award, a US ONR Young Investigator Award, an IFAC World Congress Young Author Prize, a World Haptics Conference Best Paper Award, and IEEE Fellow. Selected current activities include being an IEEE Control Systems Society (CSS) Distinguished Lecturer, a member of the IEEE CSS Board of Governors, and General Chair for the 2013 American Control Conference. She was a member (2010-2011) of the US Defense Science Study Group, and she was also the founding Scientific Director (2007-2011) for the Center for Research and Education in Wind (CREW), a multi-institutional wind energy center involving the University of Colorado Boulder, the US National Renewable Energy Laboratory, Colorado School of Mines, and Colorado State University, in partnership with the US National Center for Atmospheric Research and the US National Oceanic and Atmospheric Administration.

[2012.05.17] Lecture: Control and Optimization In Cyberphysical Systems: From sensor networks to "smart parking" app. Professor Christos G. Cassandras Boston University

Time: 15:00-17:00 p.m., May 17th, Thu.

Location: RM. 511 Main Building

Abstract:

Sensor networks are multi-agent systems consisting of distributed nodes that cooperate to meet a common objective, often in an uncertain environment. Viewed as a cyber physical control system, a sensor network encompasses three interconnected functionalities: coverage, data source detection, and data collection. We will describe an optimization framework for controlling the location and movement of nodes so as to combine these functionalities. We also address the issue of information exchange among nodes aiming to minimize inter-node communication. We show that event-driven, rather than synchronous, communication can guarantee convergence to optimal solutions while drastically reducing the need for inter-node communication, thus also reducing energy consumption and extending the network's lifetime.

Despite significant advances, these systems remain largely used for data collection from physical sources. There has been limited progress on the processing of data to drive actuation and form a complete closed-loop cyber physical control system. We describe one such system recently developed for dynamic resource allocation in an urban environment. Termed a Smart parking system, it dynamically assigns and reserves an optimal resource (parking space) for a user (driver) based on an objective function that combines proximity to destination and parking cost, while also ensuring that the overall parking capacity is efficiently utilized. When an optimal allocation is updated, it is guaranteed to avoid reservation conflicts and to preserve a monotonically non-increasing cost for every user relative to current assignment. We will describe an implementation of this system at a Boston University parking facility based on driver requests entered through a smart phone app.

Biography of Prof. Christos G. Cassandras

Christos G. Cassandras is Head of the Division of Systems Engineering and Professor of Electrical and Computer Engineering at Boston University. He is also co-founder of Boston University Center for Information and Systems Engineering (CISE). He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published over 300 refereed papers in these areas, and five books. He has guest-edited several technical journal issues and serves on several journal Editorial Boards. He has recently collaborated with The MathWorks, Inc. in the development of the discrete event and hybrid system simulator SimEvents.

Dr. Cassandras was Editor-in-Chief of the IEEE Transactions on Automatic Control from 1998 through 2009 and has also served as Editor for Technical Notes and Correspondence and Associate Editor. He is the 2012 President of the IEEE Control Systems Society (CSS) and has served as Vice President for Publications and on the Board of Governors of the CSS. He has chaired the CSS Technical Committee on Control Theory, and served as Chair of several conferences. He has been a plenary speaker at many international conferences, including the American Control Conference in 2001 and the IEEE Conference on Decision and Control in 2002, and an IEEE Distinguished Lecturer.

He is the recipient of several awards, including the 2011 IEEE Control Systems Technology Award, the Distinguished Member Award of the IEEE Control Systems Society (2006), the 1999 Harold Chestnut Prize (IFAC Best Control Engineering Textbook) for Discrete Event Systems: Modeling and Performance Analysis, a 2011 prize for the IBM/IEEE Smarter Planet Challenge competition, a 1991 Lilly Fellowship and a 2012 Kern Fellowship. He is a member of Phi Beta Kappa and Tau Beta Pi. He is also a Fellow of the IEEE and a Fellow of the IFAC.

[2011.12.14] Lecture: Are Stochastic Dynamics the Foundation of Intelligence? Prof. Weibo Gong, UMass

Professor Weibo Gong, Department of Electrical and Computer Engineering, Department of Computer Sciences, University of Massachusetts, Amherst.

Time: At the 50th CDC 12/11-15/2011, Wednesday Dec. 14, 1:30 PM

Abstract: Concept abstraction is an important component of intelligence. Scientists today still do not know how the brain accomplishes it. In this talk we compare some recent mathematical results about random walks on manifolds and graphs with the features of concept abstraction processes to seek understanding of the algorithms involved.

[2010.05.21] Lecture: Constructing Spatial Barriers with Underwater Sensor Networks, Prof. Jie Wang, UMass

Time: 10:00-12:00, May 26th, Wednesday

Location: 1-415, FIT Building, Tsinghua University

Abstract: Constructing Spatial Barriers with Underwater Sensor Networks

Current technologies have made it possible for submarines to thwart standard (active or passive) sonar detections. One viable alternative is to use magnetic or acoustic sensors in close proximity to possible underwater pathways a submarine may pass through. This approach requires deploying large-scale underwater sensor networks to form a spatial barrier. In this talk we will first survey technologies of underwater acoustic networks and 2-dimensional sensor networks. We will then show new results for 3-dimensional sensor networks which are fundamentally different. We first prove that spatial barrier is unlikely to exit in a large 3-dimensional fixed emplacement sensor field where sensor locations follow a Poisson point process. In other words, a path is likely to exit by which an adversary informed of the locations of the sensors can pass through without being detected. We then describe energy conserving approaches to constructing a spatial barrier using mobile nodes so that intruding submarines cannot pass through without being detected. We start by implementing an optimal approach to mapping sensors to grid positions. We then focus on developing an approximate solution for better time efficiency using Auction algorithms and a divide-and-conquer strategy. Our results show that the Auction algorithm produces similar results to the optimal approach at a reduced computational expense, providing an effective approach to constructing an underwater spatial barrier.

This is joint work with Benyuan Liu and Stanley Barr.

Biography of Prof. Jie Wang

Dr. Jie Wang is Professor and Chair of the Department of Computer Science at the University of Massachusetts, Lowell, USA. He is also Director of the Center for Network and Information Security in the university and co-Director of Cyber Forensics Lab in the department. He received his PhD in Computer Science from Boston University in 1991, Master of Engineering in Computer Science from Zhongshan University in 1985, and Bachelor of Sciences in Computational Mathematics from Zhongshan University in 1982. His research interests include computational complexity theory, combinatorial optimization algorithms, computational medicine, and network security. He has worked as a security consultant in financial industry. His recent research focus is on network dynamics, knowledge discovery, and wireless sensor networks. His research has been funded by the NSF since 1991. IBM, Intel, Google and the Natural Science Foundation of China have also funded his research. He has published over 120 research papers in some of the most prestigious journals and conference proceedings. He has authored and co-authored three books; edited and co-edited four books. He is active in professional service, including chairing conference program committees, serving as journal editors, and organizing conferences and workshops.

[2009.12.21] Lecture: Can we bridge the knowledge from different fields?, Prof. Weibo Gong, UMass

Time: 3:30pm. December 23th, Wednesday

Location: Multifunction Auditorium, FIT Building, Tsinghua University

[2009.12.09] Lecture: A Personal Account of the Past, Present, and Future of Control Theory and Systems giving the Experience from 1959-2009, Prof. Yu-Chi Ho, Harvard University

Time: 10:30am-11:30am. December 11th, Friday

Location: Room 511, Central Building, Tsinghua University

Abstract: A Personal Account of the Past, Present, and Future of Control Theory and Systems giving the Experience from 1959-2009

I shall use my personal experience from 1959-2009 to illustrate in a bigger context the history and future prospects of this relatively mature discipline.

Biography of Prof. Yu-Chi Ho

Prof. Yu-Chi Ho received his S.B. and S.M. degrees in Electrical Engineering from M.I.T. and his Ph.D. in Applied Mathematics from Harvard University. Except for three years of full time industrial work he has been on the Harvard faculty. Since 1969 he has been Gordon McKay Professor of Engineering and AppliedMathematics. In 1988, he was appointed to the T. Jefferson Coolidge Chair in Applied Mathematics and Gordon McKay Professor of Systems Engineering at Harvard and as visiting professor to the Cockrell Family Regent Chair in Engineering at the University of Texas, Austin. In 2001, he retired from teaching duties at Harvard and became a Research Professor (2001-2006) and also was appointed to be a chair professor and chief scientist (part time), at the Center for Intelligent and Networked Systems (CFINS), Department of Automation, Tsinghua University, Beijing China.

[2009.12.08] Distinguished Engineer Lecture: Challenges and Opportunities in Efficient Energy Production, Consumption and Transmission, Prof. Xiaohong Guan, Tsinghua University

Time: 2:00pm-3:30pm. December 10th, Uconn

Location: ITEB 336, Uconn

Biography of Xiaohong Guan(Ph.D. Electrical & Computer Engineering, University of Connecticut)

Dr. Xiaohong Guan is the Cheung Kong Professor of Systems Engineering and Dean of the School of Electronic and Information Engineering of Xi'an Jiaotong University. He is also an adjunct professor and Director of the Center for Intelligent and Networked Systems at Tsinghua University, Beijing and served as department head (2003-2008). Dr. Guan has made seminal contributions in the areas of scheduling and optimization of large scale electrical power and manufacturing systems; game theoretic analysis and bidding strategies of electric power markets; and computer network security. He holds five patents and has published four books and book chapters along with more than 160 scholarly journal articles and conference proceedings. Dr. Guan is an IEEE Fellow. He is serving as a Distinguished Lecturer of IEEE RAS, Editor of IEEE Transactions on Power Systems, and Associate Editor of Automatica.

Detailed ScheduleUCONN DISTINGUISHED ENGINEERING AWARDS EVENT SCHEDULE

[2009.07.06] Lecture: Polyhedral Approximations in Convex Optimization, Prof. Dimitri P. Bertsekas, M.I.T.

Time: 10:00am. July 9th, Thu.

Location: Room 511, Central Building, Tsinghua University

Abstract: Polyhedral Approximations in Convex Optimization

We propose a unifying framework for solution of convex programs by polyhedral approximation. It includes classical methods, such as cutting plane, Dantzig-Wolfe decomposition, bundle, and simplicial decomposition, but also includes recrements of these methods, as well as new methods that are well-suited for important large-scale types of problems, arising for example in network optimization.

Biography of Prof. Dimitri P. Bertsekas

Dimitri P. Bertsekas received his undergraduate degree in engineering from the National Technical University of Athens, Greece, and his Ph.D. from the Massachusetts Institute of Technology.

Dr. Bertsekas has held faculty positions with the Engineering-Economic Systems Dept., Stanford University (1971-1974) and the Electrical Engineering Dept. of the University of Illinois, Urbana(1974-1979). Since 1979 he has been teaching at the Electrical Engineering and Computer Science Department of the Massachusetts Institute of Technology (M.I.T.), where he is currently McAfee Professor of Engineering. He consults regularly with private industry and has held editorial positions in several journals. His research at M.I.T. spans several fields, including optimization, control, large-scale computation, and data communication networks, and is closely tied to his teaching and book authoring activities. He has written numerous research papers, and fourteen books, several of which are used as textbooks in MIT classes.

Professor Bertsekas was awarded the INFORMS 1997 Prize for Research Excellence in the Interface Between Operations Research and Computer Science for his book "Neuro-Dynamic Programming" (co-authored with John Tsitsiklis), the 2000 Greek National Award for Operations Research, and the 2001 ACC John R. Ragazzini Education Award. In 2001, he was elected to the United States National Academy of Engineering.

Dr. Bertsekas' recent books are "Dynamic Programming and Optimal Control: 3rd Edition" (2007), "Introduction to Probability: 2nd Edition" (2008), and Convex Optimization Theory (2009), all published by Athena Scientific.

Besides his professional activities, Professor Bertsekas is interested in travel, portrait, and landscape photography. His pictures have been exhibited on several occasions at M.I.T., and can also be accessed from his www site.