The 2009 CDC/CCC thanks Gold Sponsors

Shanghai 2009
December 16 - 18

Sponsoring Organizations

Technical Program Details

Technical program details are available on the PaperPlaza website:

Bode Lecture, Plenaries, Semi-Plenaries

Aside from the technical sessions, the 2009 CDC will feature three plenary lectures, four semi-plenary lectures and the Bode Lecture. The 2009 Bode Lecture will be presented by Prof. Peter C. Caines of McGill University. The Plenary speakers will be Prof. Roger W. Brockett of the Harvard University, Professor P.R. Kumar of the University of Illinois, and Professor Tzyh Jong Tarn of the Washington University. The semi-plenary speakers will be Prof. Ali Jadbabiae of the University of Pennsylvania, Prof. Anders Lindquist of KTH Sweden, Prof. Pengfei Yao of the Chinese Academy of Sciences, and Prof. Wing Shing Wong of the Chinese University of Hong Kong.

CDC Bode Lecture, Plenaries and Semi-Plenaries:
Bode Lecture: The Bode Lecture will be on Friday, Dec. 18 in the Grand Ballroom I.
The lecture slides can be downloaded here.
  • Peter E. Caines. Friday Dec. 18, 2009. Grand Ballroom I
    Bode Lecture Title: Mean Field Stochastic Control

    Bode Lecture Abstract. This talk presents the Mean Field (or Nash Certainty Equivalence (NCE)) methodology initiated with Min-Yi Huang and Roland Malhamé for the analysis and control of large population stochastic dynamic systems. Optimal control problems for multi-agent stochastic systems, in particular those with non-classical information patterns and those with intrinsic competitive behavior, are in general intractable. Inspired by mean field approximations in statistical mechanics, we analyse the common situation where the dynamics and rewards of any given agent are influenced by certain averages of the mass multi-agent behavior. The basic result is that classes of such systems possess game theoretic (Nash) equilibria wherein each agent employs feedback control laws depending upon both its local state and the collectively generated mass effect. In the infinite population limit the agents become statistically independent, a phenomenon related to the propagation of chaos in mathematical physics.

    Explicit solutions in the linear quadratic Gaussian (LQG) - NCE case generalize classical LQG control to the massive multi-agent situation, while extensions of the Mean Field notion enable one to analyze a range of problems in systems and control. Specifically, generalizations to nonlinear problems may be expressed in terms of controlled McKean-Vlasov Markov processes, while localized (or weighted) mean field extensions, the effect of possible major players and adaptive control generalizations permit applications to microeconomics, biology and communications; furthermore, the standard equations of consensus theory, which are of relevance to flocking behavior in artificial and biological systems, have been shown to be derivable from the basic LQG - NCE equations. In the distinct point process setting, the Mean Field formulation yields call admission control laws which realize competitive equilibria for complex communication networks.

    In this talk we shall motivate the Mean Field approach to stochastic control, survey the current results in the area by various research groups and make connections to physics, biology and economics.

    This talk presents joint work with Minyi Huang and Roland Malhamé, and Arman Kizilkale, Arthur Lazarte, Zhongjing Ma and Mojtaba Nourian.

    Biography. Peter Caines received the BA in mathematics from Oxford University in 1967 and the PhD in systems and control theory in 1970 from Imperial College, University of London, where his supervisor was D. Q. Mayne, FRS. After periods as a postdoctoral researcher and faculty member at UMIST, Stanford, UC Berkeley, Toronto and Harvard, he joined McGill University, Montreal, in 1980, where he is James McGill Professor and Macdonald Chair in the Department of Electrical and Computer Engineering.

    Peter Caines is a Fellow of the IEEE, SIAM and the Canadian Institute for Advanced Research, and was elected to the Royal Society of Canada in 2003. In 2000 the adaptive control paper he coauthored with G. C. Goodwin and P. J. Ramadge (IEEE Transactions on Automatic Control, 1980) was recognized by the IEEE Control Systems Society as one of the 25 seminal control theory papers of the 20th century. Peter Caines has served as an Associate Editor of the IEEE Transactions on Automatic Control, the IEEE Transactions on Information Thoory and the SIAM Journal on Control and Optimization; during 1992 - 95 he served on the Board of Governors of the IEEE Control Systems Society, was a Member of the Scientific Advisory Board of the Max Plank Society, 2002 - 2007 and the EU HYCON Review Committee, 2005 - 2007. Peter Caines is the author of Linear Stochastic Systems, John Wiley, 1988, and is the co-editor of several volumes of papers on stochastic systems. His research interests include the areas of system identification, adaptive control, logic control and discrete event systems. Recently his activities have focused on hybrid systems theory, and stochastic multi-agent and distributed systems theory, together with their links to physics, economics and biology.
  • Roger W. Brockett. Wednesday Dec. 16, 2009. Grand Ballroom I
    Plenary Title: Poisson Processes and the Design of Finite State Controllers

    Plenary Abstract. It is widely recognized that many of the most important challenges faced by control engineers involve the development of methods to design and analyze systems having components most naturally described by differential equations interacting with components best modeled using sequential logic. This situation can arise both in the development of high volume, cost sensitive, consumer products and in the design and certification of one of a kind, complex and expensive systems. The response of the control community to this challenge includes work on limited communication control, learning control, control languages, and various efforts on hybrid systems. This work has led to important new ideas but progress has been modest and the more interesting results seem to lack the kind of unity that would lead to a broadly inclusive theory. In this talk we describe an approach to problems of this type based on sample path descriptions of finite state Markov processes and suitable adaptations of known results about linear systems. The result is an insightful design technique yielding finite state controllers for systems governed by differential equations. We illustrate with concrete examples.

    Biography. Roger Brockett is the An Wang professor of electrical engineering and Computer Science at Harvard University. He has been exploring questions in engineering and applied sciences since starting graduate school, and has been teaching since his appointment as an Assistant Professor at MIT in 1963. His contributions include early work on frequency domain stability theory (multipliers), circle criterion instability, differential geometric methods in nonlinear control, feedback linearization and stabilization, the computation of Volterra series, a Lie algebra approach to the sufficient statistics problem in nonlinear estimation, work on robot kinematics and dynamics, formal languages for motion control, hybrid systems, flows for computation related to integrable systems, sub-Riemannian geometry, minimum attention control, quantum control, quantized systems and, most recently, optimal control of Markov processes. He is a fellow of the IEEE and of SIAM, has received awards from IEEE (Control Systems Science and Engineering), ASME (Oldenberger), SIAM (Reid Prize), and AACC (Eckman, and Bellman), is a member of the US National Academy of Engineering. He is this year recipient of the IEEE Leon Kirchmayer Award for Graduate Education. He has directed approximately 60 Ph.D. theses and authored about 200 research papers.
  • P.R. Kumar. Wednesday Dec. 16, 2009. Grand Ballroom I
    Plenary Title: Towards a System Theoretic Foundation for Control over Networks

    Plenary Abstract. We address several issues that are important for developing a comprehensive understanding of the problems of control over networks. Proceeding from bottom to top, we describe theoretical frameworks to study the following issues, and present some answers:

  • (i) Network information theory:
    Are there limits to information transfer over wireless networks? How should nodes in a network cooperate to achieve information transfer?
  • (ii) In-network information processing:
    How should data from distributed sensors be fused over a wireless network? Can one classify functions of sensor data vis-a-vis how difficult they are to compute over a wireless network?
  • (iii) Real-time scheduling over wireless networks:
    How should packets with hard deadlines be scheduled for transmission over unreliable nodes? What QoS guarantees can be provided with respect to latencies and throughputs?
  • (iv) Clock synchronization over wireless networks:
    What are the ultimate limits to synchronization error? How should clocks be synchronized?
  • (v) System level guarantees in networked control:
    How can one provide overall guarantees on of networked control systems that take into account hybrid behavior, real-time interactions, and distributed aspects?
  • (vi) Abstractions and architecture:
    What are appropriate abstractions, and what is an appropriate architecture, to simplify networked control system design and deployment?

    Biography. P. R. Kumar obtained his B. Tech. degree in Electrical Engineering (Electronics) from I.I.T. Madras in 1973, and the M.S. and D.Sc. degrees in Systems Science and Mathematics from Washington University, St. Louis, in 1975 and 1977, respectively. From 1977-84 he was a faculty member in the Department of Mathematics at the University of Maryland Baltimore County. Since 1985 he has been at the University of Illinois, Urbana-Champaign, where he is currently Franklin W. Woeltge Professor of Electrical and Computer Engineering, Research Professor in the Coordinated Science Laboratory, Research professor in the Information Trust Institute, and Affiliate Professor of the Department of Computer Science.

    He has worked on problems in game theory, adaptive control, stochastic systems, simulated annealing, neural networks, machine learning, queueing networks, manufacturing systems, scheduling, and wafer fabrication plants. His current research interests are in wireless networks, sensor networks, and networked embedded control systems. He has received the Donald P. Eckman Award of the American Automatic Control Council, the IEEE Field Award in Control Systems, and the Fred W. Ellersick Prize of the IEEE Communications Society. He is a Fellow of the IEEE, and member of the US National Academy of Engineering. He was awarded a Doctor of Science, Honoris Causa, by Eidgenossische Technische Hochschule, Zurich in 2008.
  • Tzyh Jong Tarn. Friday Dec. 18, 2009. Grand Ballroom I
    Plenary Title: New Opportunities for Control: Quantum Internal Model Principle and Decoherence Control

    Plenary Abstract. Decoherence, which is caused due to the interaction of a quantum system with its environment plagues all quantum systems and leads to the loss of quantum properties that are vital for quantum computation and quantum information processing. Superficially, this problem appears to be the disturbance decoupling problem in classical control theory. In this talk first we briefly review recent advances in Quantum Control. Then we propose a novel strategy using techniques from geometric systems theory to completely eliminate decoherence and also provide conditions under which it can be done so. A novel construction employing an auxiliary system, the bait, which is instrumental to decoupling the system from the environment, is presented. This literally corresponds to the Internal Model Principle for Quantum Mechanical Systems which is quite different from the classical theory due to the quantum nature of the system. Almost all the earlier work on decoherence control employ density matrix and stochastic master equations to analyze the problem. Our approach to decoherence control involves the bilinear input affine model of quantum control system which lends itself to various techniques from classical control theory, but with non-trivial modifications to the quantum regime. This approach yields interesting results on open loop decouplability and Decoherence Free Subspaces (DFS). The results are also shown to be superior to the ones obtained via master equations. Finally, a methodology to synthesize feedback parameters itself is given, that technology permitting, could be implemented for practical 2-qubit systems performing decoherence free Quantum Computing. Open problems and future directions in quantum control also will be discussed.

    Biography. He is currently a Professor in the Department of Electrical and Systems Engineering and the Director of the Center for Robotics and Automation at Washington University. He also is the director of the Center for Quantum Information Science and Technology at Tsinghua University. An active member of the IEEE Robotics and Automation Society, Dr. Tarn served as the President of the IEEE Robotics and Automation Society, 1992-1993, the Director of the IEEE Division X (Systems and Control), 1995-1996, and a member of the IEEE Board of Directors, 1995-1996. He is the first recipient of the Nakamura Prize at the 10th Anniversary of IROS in Grenoble, France, 1997, the recipient of the prestigious Joseph F. Engelberger Award of the Robotic Industries Association in 1999, the Auto Soft Lifetime Achievement Award in 2000, the Pioneer in Robotics and Automation Award in 2003 from the IEEE Robotics and Automation Society, and the George Saridis Leadership Award from the IEEE Robotics and Automation Society in 2009. He was featured in the Special Report on Engineering of the 1998 Best Graduate School issue of US News and World Report and his recent research accomplishments were reported in the Washington Times, Washington D.C., the Financial Times, London, Le Monde, Paris, and the Chicago Sun-Times. Dr. Tarn is a Fellow of IEEE and an IFAC Fellow.
    Semi-Plenaries: We will have four semi-plenaries on Thursday, Dec. 17 in Grand Ballroom I and Auditorium.
  • Ali Jadbabaie. Thursday Dec. 17, 2009. Grand Ballroom I
    Semi-Plenary Title: Information Aggregation in Complex Dynamic Networks

    Semi-Plenary Abstract. Over the past few years there has been a rapidly growing interest in analysis, design and optimization of various types of collective behaviors in networked dynamic systems. Collective phenomena (such as flocking, schooling, rendezvous, synchronization, and agreement) have been studied in a diverse set of disciplines, ranging from computer graphics and statistical physics to distributed computation, and from robotics and control theory to social sciences and economics. A common underlying goal in such studies is to understand the emergence of some global phenomena from local rules and interactions. In this talk, I will expand on such developments and present new models for information aggregation tailored to social networks that go beyond existing "consensus-based" models. Motivated by such approaches, I will present a set of new tools and modeling abstractions for analysis and design of large scale dynamic networks based on ideas from algebraic topology and spectral random graph theory. Finally, I present some open problems and challenges.

    Biography. Ali Jadbabaie received his BS degree (with High honors) in Electrical Engineering from Sharif University of Technology in 1995. He received a Masters degree in Electrical and Computer Engineering from the University of New Mexico, Albuquerque in 1997and a Ph.D. degree in Control and Dynamical Systems from California Institute of Technology in 2001. From July 2001-July 2002 he was a postdoctoral associate at the department of Electrical Engineering at Yale University. Since July 2002 he has been with the department of Electrical and Systems Engineering and GRASP Laboratory at the University of Pennsylvania, Philadelphia, PA, where he is now an associate professor. He is a recipient of an NSF Career Award, an ONR Young Investigator award, Best student paper award of the American Control Conference 2007, the O Hugo Schuck Best Paper award of the American Automatic Control Council, and the George S. Axelby Outstanding Paper Award of the IEEE Control Systems Society. His research is broadly in network science, specifically, analysis, design and optimization of networked dynamical systems with applications to multi-robot formation control, social aggregation and other collective phenomena.
  • Anders Lindquist. Thursday Dec. 17, 2009. Auditorium
    Semi-Plenary Title: What are moment problems and why are they useful in systems and control?

    Semi-Plenary Abstract. Moment problems are ubiquitous throughout engineering, mathematics and science, and particularily at their interface. Power moments of probability measures play an important role in partial statistical modeling and in its application to information theory, communications, signals and systems. Applications of the trigonometric moment problem to systems and control also have a long and fruitful history, including the rational covariance extension problem for modeling a finite time window of a stochastic process. Analytic interpolation problems are an important class of moment problems with applications to circuit theory, power systems, robust control, signal processing, spectral estimation and stochastic realization theory. Moment problems are typically underdetermined and give rise to families of particular solutions, and finding a solution that also satisfies a natural optimality criterion or design specification is an important general problem. In this lecture we pose and solve a nonclassical version of this problem (which we call the moment problem for positive rational measures) that reflects the importance of rational functions in signals, systems and control. While this version of the problem is decidedly nonlinear, there exists a natural, universal family of strictly convex optimization criteria defined on the convex set of particular solutions. This provides a powerful paradigm for smoothly parameterizing, comparing and shaping the solutions based on various additional design criteria. It also enables us to establish the smooth dependence of solutions on problem data. During this lecture, we will motivate and illustrate these results by applications to robust control and signal processing.

    Biography. Anders Lindquist received the Ph.D. degree in 1972 from the Royal Institute of Technology, Stockholm, Sweden. From 1972 to 1974 he held visiting positions at the University of Florida and Brown University. In 1974 he became an Associate Professor, and in 1980 a Professor at the University of Kentucky, where he remained until 1983. He is now a Professor at the Royal Institute of Technology, where in 1982 he was appointed to the Chair of Optimization and Systems Theory. Presently, he is the Head of the Mathematics Department and the Director of the Strategic Research Center for Industrial and Applied Mathematics, both at the Royal Institute of Technology. Dr. Lindquist is a Member of the Royal Swedish Academy of Engineering Sciences, a Foreign Member of the Russian Academy of Natural Sciences, an Honorary Member the Hungarian Operations Research Society, and a Fellow of the IEEE. He was awarded the 2009 W.T. and Idalia Reid Prize in Mathematics from the Society for Industrial and Applied Mathematics (SIAM). He was also the recipient (together with C. I. Byrnes and T. T. Georgiou) of the George S. Axelby Outstanding Paper Award of the IEEE Control Systems Society (CSS) for the year 2003. He is presently chair of the CSS Fellow Nomination Committee.
  • Wong Wing Shing. Thursday Dec. 17, 2009. Auditorium
    Semi-Plenary Title: Target Choice, Control Energy, and Communication Complexity: Facets of an Information-Based Distributed Control Systems

    Semi-Plenary Abstract. Intuitively, it seems easy to convince oneself that there should be an intimate connection between information and control. However, exact quantification of this connection remains elusive, due partly to its complexity. Recent research on information-based control has shed some light on the interaction between control of a dynamical system and the information on which the control strategies are based on, particularly on the issue of communication data rate and stability control. In this talk, we describe a fundamental relationship that links control objectives, control energy, and information together in a distributed control system. We will explain concepts such as control communication complexity, adopted from distributed computing, and control energy cost. We will show how these concepts are related. Connections to quantum control and large networks will be highlighted as examples. Part of the work reported in the talk has been done jointly with John Baillieul. Related papers can be found in

    Biography. WONG Wing Shing graduated from Yale University with a combined MS and BA degree and obtained MS and PhD degrees from Harvard University. He is an IEEE Fellow and a Fellow of the Hong Kong Institution of Engineers (FHKIE). He joined the Chinese University of Hong Kong after working for ten years at AT&T Bell Laboratories and is now a Professor of Information Engineering. He was the Chairman of the Information Engineering Department from 1995 to 2003. He has been serving as the Dean of the Graduate School since 2005. His research interests include wireless communication and information-based control systems. He served as the Science Advisor at the Innovation and Technology Commission in the Hong Kong SAR Government from 2003 to 2005 and served from 2006 to 2008 as a Board Director and the Chairman of the Technical Committee of ASTRI, an applied research institute founded by the Hong Kong SAR Government. He served as an Associate Editor of the IEEE Transactions on Automatic Control for four years. He has co-founded an international journal, Communications in Information and Systems, and is now serving as the co-Editor-in-Chief.
  • Pengfei Yao. Thursday Dec. 17, 2009. Grand Ballroom I
    Semi-Plenary Title: Differential Geometric Approach in Control and Modeling of Vibrational Mechanics

    Semi-Plenary Abstract. The control and modeling of vibration systems such as, waves, plates and shells is difficult, particularly when those systems contain variable coefficients or are made up of nonlinear materials. This talk describes recent theoretical advances in control of vibration systems using geometric methods whch have been created to cope with the following two situations: (i) The case where the dynamic systems are variable in space; (ii) the case where the dynamic systems themselves evolve on curved surfaces. In particular, the geometric methods provide checkable conditions on exact controllability and stabilization for wave and plate systems with variable coefficients. They offer intrinsic mathematical models for shells. From these, observability estimates for shells can be established. The approach allows for the use of a computational energy method in the Riemannian metric enabling the control analysis of the quasilinear wave equation to be carried out. For further information, see:

    The support of the National Science Foundation of China is gratefully acknowledged.

    Biography. Peng-Fei Yao recived the Ph. D. in Academy of Mathematics & System Sciences, Chinese Academy of Sciences in 1994. Since November 1998, he has been with Academy of Mathematics & System Sciences, Chinese Academy of Sciences, where he is a professor in applied mathematics. His research interests have often focused on the theoretical aspects of control and modeling for vibrational mechanics, such as waves, plates, and shells, including geometric methods for systems with variable coefficient and nonlinear materials.

    Key dates

    Corporate Sponsors
    Become a "Gold/Silver/Bronze Sponsor"
    for 48th CDC and
    Place your banner here

    Gold Sponsors

    Silver Sponsors

    Bronze Sponsors

    Initial submissions beginJan. 2, 2009
    Invited session proposals closeMar. 6, 2009
    All paper submissions close Mar. 6, 2009
    Acceptance notificationJuly, 2009
    Final submissions begin Aug 1, 2009
    Registration openAug 1, 2009
    Final submission closeSept. 9, 2009