Technical program details are available
on the PaperPlaza website:
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:
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.
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
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.
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
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
(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?
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
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
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.
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.
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
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
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.
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
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
Anders Lindquist. Thursday Dec. 17, 2009. Auditorium
What are moment problems and why are they useful in systems and control?
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.
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
Target Choice, Control Energy, and Communication Complexity:
Facets of an Information-Based Distributed Control Systems
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
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
Differential Geometric Approach in Control and Modeling of Vibrational Mechanics
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: http://lsc.amss.ac.cn/~pfyao/selectedpaper.htm.
The support of the National Science Foundation of China is gratefully acknowledged.
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.
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|Initial submissions begin||Jan. 2, 2009
|Invited session proposals close||Mar. 6, 2009
|All paper submissions close
||Mar. 6, 2009
|Acceptance notification||July, 2009
|Final submissions begin ||Aug 1, 2009
|Registration open||Aug 1, 2009
|Final submission close||Sept. 9, 2009