- they apply to general nonlinear systems with disturbances;
- we obtain explicit (often non-conservative) bounds on the maximal allowable transmission interval that guarantee stability;
- and we show that this approach is valid for a wide range of network protocols. This provides a flexible framework for design of NQCS, NCS and/or QCS that is amenable to various extensions and modifications, such as a treatment of dropouts and stochastic protocols, combined controller/protocol design, and so on.
Richard H. Middleton
Professor Richard H. Middleton was born on 10th December 1961 in Newcastle Australia. He received his B.Sc. (1983), B.Eng. (Hons-I)(1984) and Ph.D. (1987) from the University of Newcastle, Australia. He has had visiting appointments at the University of Illinois at Urbana-Champaign, the University of Michigan and the Hamilton Institute (National University of Ireland Maynooth). In 1991 he was awarded the Australian Telecommunications and Electronics Research Board Outstanding Young Investigator award. In 1994 he was awarded the Royal Society of New South Wales Edgeworth-David Medal, and the M.A. Sargent Award from the Electrical College of Engineers Australia in 2004. He has served as an associate editor of the IEEE Transactions on Automatic Control, the IEEE Transactions on Control System Technology, and Automatica, as Head of Department of Electrical and Computer Engineering at the University of Newcastle; as a panel member and sub panel chair for the Australian Research Council; as Vice President - Member Activities of the IEEE Control Systems Society, and as Director of the ARC Centre for Complex Dynamic Systems and Control. He was elected to the grade of Fellow of the IEEE starting 1999. He is currently a Research Professor at the Hamilton Institute, The National University of Ireland, Maynooth; a Senior Research Associate of the University of Newcastle; Vice President (Conference Activities) of the IEEE Control System Society and an Associate Editor at Large of the IEEE Transactions on Automatic Control. His research interests include a broad range of Control Systems Theory and Applications.
LECTURES
i) ‘String Stability’ Issues in Distributed Control Systems
Distributed control systems, where dynamic interactions must be countered by local feedback control based on partial information, is a challenging research area. One problem in this context has been known as ‘String Instability’ may arise in long ‘chains’ of distributed control systems. This long chain structure may arise in a range of applications including intelligent vehicle highway systems, distributed irrigation channel control, and also in supply chain management, where problems closely related to string instability have been known as the ‘Forrester’ or ‘Bullwhip’ effect.
String stability issues may be analysed from the perspective of performance limitations in feedback control systems with a type II servo response. In this case, there are complex analytic results, analogous to the Bode Sensitivity Integral, that apply to the complementary sensitivity function. In this talk, I will review this background; show some extensions to the results for heterogeneous systems; systems with type I response and systems with limited range communications.
ii) Control, Communications and limited information feedback
There has recently been increased interest in studying feedback control problems in which the communication of signals of interest is imperfect. One way of representing such signal imperfections is to use information theoretic concepts to describe limited communication rates. This gives rise to an interesting new set of theoretical problems, including requirements on communication rate required to achieve stabilisation and performance. In some cases, communication rate limitations can be cast as a power limit on the signal transmitted across an additive Gaussian channel, and therefore as a ‘signal to noise ratio’ limit. In several cases of interest, these give rise to interesting H2 optimal control problems.
iii) Systems biology: What does Systems & Control Theory have to offer Biology?
‘Systems Biology’ can be defined as the application of dynamic systems ideas to research the systems that describe the mechanisms of life. Not only does this give opportunity for application of existing dynamic systems research, but it also poses new fundamental problems in the analysis of dynamic systems. Beyond this however, it is important to consider the potential impact of this area on biology. In this talk, I take several examples of systems and control results, and show how they contribute to new biological understandings.
iv) Autonomous Soccer Robotics -
RoboCup soccer is an international initiative aimed at fostering robotics and artificial intelligence research. It has been operating for over a decade now, and there are many different divisions and competitions within this organisation. In this talk, based on our experience in the Standard Platform League, I will describe how some concepts from systems and control can be applied to this area, and the results achieved with these. Examples of techniques used include: optimisation; extended Kalman Filters, ‘soft decision’ processes in image classification, and the use of potential fields for behaviour decisions. The talk will include video footage from relevant games and discussions of difficulties encountered and solved as part of the competition, together with new challenges in Humanoid divisions of RoboCup.
Top of the page
Dragan Nesic
Dragan Nesic obtained his BE (Mech) in 1990 from the University of Belgrade (former Yugoslavia) and his PhD in 1997 from the Australian National University (Australia). Currently, he is a Professor at The Electrical Engineering Department, University of Melbourne, Australia. His research interests are in a broad area of nonlinear systems, including sampled-data, networked and quantized control systems, averaging, singular perturbations and extremum seeking control. Prof. Nesic has published about 200 journal and conference papers in these areas. He is a recepient the Australian Professorial Fellowship (2004-2009) and the Humboldt Fellowship (2003-2004). He has served as an Associate Editor for IEEE Transactions on Automatic Control , Automatica, Systems and Control Letters and European Journal of Control. Prof. Nesic is a Fellow of IEEE and a Fellow of IEAust. He was invited to present semi-plenary lectures at NOLCOS 2007 and Chinese Conference on Decision and Control 2008.
LECTURES
Talk 1:
Title : Analysis and design of extremum seeking controllers
Abstract:
Design of engineered systems whose operation is "best" or "optimal" in some sense is increasingly important due to a range of socio-economic and environmental problems that we are facing at the dawn of the 21st century, such as the climate change and increased competition in a global market. While still attracting a considerable research attention, optimal control methods can be regarded as classical and in certain areas, such as linear quadratic control, they are very well developed and understood. An underlying assumption in the classical control literature is that both the plant model and the cost to optimize are known to the engineer designing the system. However, surprisingly many engineering systems do not satisfy this basic assumption and, hence, classical optimization methods are often not directly applicable.
Extremum seeking is an optimal control approach that deals with situations when the plant model and/or the cost to optimize are not available to the designer but it is assumed that measurements of plant input and output signals are available. Using these available signals, the goal is to design a controller that dynamically searches for the optimizing inputs. This method was successfully applied to biochemical reactors, ABS control in automotive brakes, variable cam timing engine operation, electromechanical valves, axial compressors, mobile robots, mobile sensor networks, optical fibre amplifiers and so on. Interestingly, some bacteria (such as the flagella-actuated E. Coli) and swarms of fish collectively search for food using extremum seeking techniques. This presents opportunities for research cross-fertilization between control engineering and biology.
While extremum seeking is an old topic, local stability of a class of extremum seeking controllers was proved for the first time by Krstic and Wang in 2000. Subsequently, Popovic and Teel proposed an alternative framework for extremum seeking and provided corresponding stability proofs. We present an extension of stability results by Krstic and Wang for a simplified extremum seeking scheme and show that the scheme yields semi-global extremum seeking under appropriate assumptions if the controller parameters are tuned appropriately. An interesting trade-off between the size of domain of attraction and the speed of convergence of the scheme is uncovered. The scheme works in essence as a steepest descent method and we also provide a strategy and conditions under which it yields global stability in presence of local extrema. Flexibility of the choice of dither in the scheme is also discussed and its effect on the convergence speed is explained. We use recent results on singular perturbations and averaging in the stability analysis. Examples of application of our scheme and Teel and Popovic approach are presented respectively for biochemical reactors and Raman optical amplifiers.
Talk 2:
Title : A unified approach to analysis and design of quantized and networked control systems
Abstract:
Emerging control applications, such as drive-by-wire cars, often require some control loops to be closed over a network. Motivation for using this set-up comes from lower cost, ease of maintenance, great flexibility, as well as low weight and volume. This motivates research into control systems in which one or several control loops are closed via a network.
Currently, there are two distinct approaches to modelling the effects of the network in such systems. The first approach assumes that only a finite number of bits can be transmitted over the network at any transmission instant and the sensor/actuator values need to be appropriately quantized before they are sent over the network. We refer to such systems as quantized control systems (QCS). In another approach, network transmits sensor/actuator values in packets and it is assumed that packets are large enough to ignore quantization effects. In this case we can regard the network as a serial communication channel that transmits signals from many sensors/actuators in the control system. The main issue in such systems is that the serial communication channel has many \x{201C}nodes\x{201D} (groups of sensors and actuators) where only one node can transmit its value at any transmission time and, hence, access to the channel needs to be scheduled in an appropriate manner for a proper operation of the system. Such systems are often referred to in the literature as networked control systems (NCS).
While QCS and NCS deal with very similar issues, these systems have been treated separately in the literature with little cross-fertilization. Our goal is to present a unified approach to analysis and design of networked and quantized control systems (NQCS) that combine time scheduling and quantization. In particular, we present an emulation controller design approach where, in the first step, we design a controller ignoring the network and, in the second step, we implement the designed controller over the network with sufficiently fast transmissions and a given protocol. Our results have several features:
Talk 3
Title : Analysis and design of nonlinear sampled-data control systems
Abstract:
In the vast literature on nonlinear control design, an area that has received scant attention is sampled-data control. In this problem, a continuous time plant is typically controlled by a discrete-time feedback algorithm. A sample and hold device provides the interface between continuous time and discrete-time.
One way to address sampled-data control is to implement a continuous time control algorithm with a sufficiently small sampling period (i.e. emulation). However, the hardware used to sample and hold the plant measurements or compute the feedback control action may make it impossible to reduce the sampling period to a level that guarantees acceptable closed-loop performance. In this case, it becomes interesting to investigate the application of sampled-data control algorithms based on a discrete-time model of the process. Note that even if the continuous-time model of a nonlinear plant is known to the designer, we typically can not compute analytically an exact discrete-time model and, hence, a more realistic approach is to base the controller design on an approximate discrete-time model of the plant (e.g. Euler).
We present an overview of our work on sampled-data nonlinear systems. First, we discuss a framework for controller design for sampled-data nonlinear systems via their approximate discrete-time models that we proposed. Our conditions are very general and we illustrate with examples that if some of these conditions are relaxed it may happen that the controller stabilizes the approximate model of the plant but it destabilized the exact model for all positive sampling periods. Our results adapt the notion of "consistency" from the numerical analysis literature and exploit it in our conditions and proofs. A range of controller design methods can be developed within our framework and we present a backstepping design for strict feedback systems as an illustration. Then, we investigate different techniques for emulation and continuous-time controller redesign for sampled-data implementation. Several examples illustrate the generality and flexibility of our approach. Moreover, they illustrate that the discrete-time designs typically outperform the emulation designs in simulations.
Top of the page
Lucy Y. Pao
Lucy Y. Pao received the B.S., M.S., and Ph.D. degrees in Electrical Engineering from Stanford University, and she is currently a Professor in the Electrical and Computer Engineering Department at the University of Colorado at Boulder. She has interests in the areas of control systems (with applications to flexible structures, disk drives, tape systems, wind turbines, atomic force microscopes, and power systems),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 recent awards include a 2003 Subaru Teaching Excellence Award, the Best Commercial Potential Award at the 2004 International Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems, and the Best Paper Award at the 2005 World Haptics Conference. She was also a plenary speaker at the 2006 IEEE Conference on Decision and Control. Selected recent and current professional society activities include serving as Program Chair for the 2004 American Control Conference (ACC), an elected member of the IEEE Control Systems Society Board of Governors for 2005-2007, and a member of the 2008 IFAC Congress Young Author Prize Selection Committee. She is on the Organizing Committee for the 2010 IFAC Symposium on Mechatronic Systems, and she will also be General Chair for the 2013 ACC.
More information about Professor Pao can be found at
http://ece.colorado.edu/~pao
LECTURES
Talk 1:
Title : Combined Feedforward/Feedback Control of Flexible Structures, with Applications Ranging from Atomic Force Microscopes to Megawatt Wind Turbines
Abstract:
In the past, manipulators, machine tools, measurement and many other systems were designed with rigid structures and operated at relatively low speeds. With an increasing demand for fuel efficiency, smaller actuators, and speed, lighter weight materials are now often used in the construction of systems, making them more flexible. Flexible structures are also prevalent in space systems where lightweight materials are necessitated for fuel efficiency when carrying the structures into space. Achieving high-performance control of flexible structures is a difficult task, but one that is now critical to the success of many important applications, ranging from the shuttle remote manipulator system, satellites, wind turbines, robot manipulators, gantry cranes, disk drives, to atomic force microscopes. The unwanted vibration that results from maneuvering a flexible structure often dictates limiting factors in the performance and lifespan of the system.
We will discuss combined feedforward and feedback architectures and algorithms for controlling flexible structures. Depending upon the particular performance goals, such as tracking accuracy in a trajectory following task or rapid settle time for a point-to-point motion, there are different requirements for the controller. In many applications, the actuators and sensors are separated by the flexible structure, leading to nonminimum phase characteristics that are challenging for control. Over the last few decades, many feedback and feedforward control methods have been developed for flexible structures. We will overview and compare several of these control methods and highlight recent developments and results. We will also present advances in a few application areas that have been achieved through better control of inherent flexible structures. Finally, we shall close by discussing a number of future challenges.
Talk 2:
Title : Multisensor Fusion Algorithms for Tracking Applications, with Applications Ranging from Tracking Ground Vehicles to Aerial Vehicles to Satellites
Abstract:
In many applications, such as tactical defense, unmanned aerial vehicles, and mobile robotics, multiple sensors are used to track objects and assess the environment. Multiple sensors provide large amounts of data with which to detect, track, and identify targets of interest. Using different types of sensors to obtain information allows the strengths of one sensor type to compensate for the weaknesses of another and further provides redundance, therefore increasing system robustness.
In this talk, we will review a few multisensor fusion algorithms for tracking applications that combine measurements from multiple sensors in a consistent manner. We will then discuss some selected recent research results in developing effective methods of managing sensor resources, deriving and extending sensor fusion algorithms for distributed processing architectures, developing techniques that allow complex multisensor fusion algorithms to be evaluated and compared efficiently, and formulating methods for detecting track loss in the absence of truth data.
Talk 3
Title : Haptic Interfaces: Making Touch Interfaces More Interactive
Abstract:
Haptic interfaces enable users to feel, touch, and manipulate remote or virtual objects, and as such, haptic interfaces can facilitate human-computer and human-machine interaction in a wide range of applications ranging from scientific visualization to teleoperation to laparoscopic surgery. In this talk, we will give examples of haptic interfaces from around the world, including those we have developed in our own lab. Limitations and capabilities of current haptic interfaces will be discussed. We will also outline a number of applications of haptic interfaces, ranging from low-end applications (vibrotactile mice, joysticks) to high-end applications (medical/rehabilitation, scientific visualization). Throughout the talk, we will highlight some of our work in two areas: (1) investigating the use of haptic interfaces for scientific visualization of complex multi-dimensional data, as well as (2) developing low-cost yet high-quality multi-degree-of-freedom haptic interfaces in the hopes of expanding haptic interfaces to an even broader range of applications.
Top of the page
Frank Allgower University of Stuttgart (G)
Frank Allgower is director of the Institute for Systems Theory and Automatic Control and professor in the Mechanical Engineering Department at the University of Stuttgart in Germany.
He studied Engineering Cybernetics and Applied Mathematics at the University of Stuttgart and the University of California at Los Angeles respectively. He received his Ph.D. degree in Chemical Engineering from the University of Stuttgart. Prior to his present appointment he held a professorship in the electrical engineering department at ETH Zurich. He also held visiting positions at Caltech, the NASA Ames Research Center, the DuPont Company and the University of California at Santa Barbara.
His main interests in research and teaching are in the area of systems and control with emphasis on the development of new methods for the analysis and control of nonlinear systems. Of equal importance to the theoretical developments are practical applications and the experimental evaluation of benefits and limitations of the developed methods. Applications range from chemical process control and control of mechatronic systems to control of atomic force miscroscopes and systems biology.
At present Frank Allgower is Editor for the journal Automatica, Associate Editor of the Journal of Process Control and the European Journal of Control and is on the editorial board of several further journals including the Journals of Robust and Nonlinear Control, IET Proceedings on Control Theory and Applications, Canadian Journal of Chemical Engineering, the journal Chemical Engineering Science and the Springer Lecture Notes in Control and Information Sciences Series. Among others he serves on the scientific council of the German Society for Measurement and Control, is on the Board of Governors of the IEEE Control System Society, is chairman of the IFAC Technical Committee on Nonlinear Systems and member of the IFAC Policy Committee and has been a member of the council of the European Union Control Association.He has been organizer or co-organizer of several international conferences and has published over 150 scientific articles. Frank received several prizes for his work including the Leibniz prize, which is the most prestigious prize in science and engineering awarded by the German National Science Foundation (DFG).
http://www.ist.uni-stuttgart.de/allgower/CV.shtml
LECTURES
Talk 1:
Title:
Nonlinear Model Predictive Control: From Theory to Applications
Abstract:
In the past decade model predictive control (MPC) has become a preferred control strategy for a large number of industrial processes. The main reasons for this popularity include the ability to explicitly handle constraints and to consider multi-variable processes with potentially many manipulated and controlled variables. Even though chemical processes often display a rather pronounced nonlinearity most industrial MPC schemes are based, however, on the assumption of a linear process behavior. By allowing nonlinear models for the predictions it can be expected that an even improved behavior can be realized.
In this presentation we will give an overview over the state of the art in the area of model predictive control where we especially discuss the opportunities that can come from the extension of MPC to the nonlinear world. After a discussion of the history and impact of MPC we will outline the challenges and solution approaches in nonlinear MPC. With a number of applications we will demonstrate that by using specially tailored optimization methods even large problems, having hundreds of states, can be controlled efficiently using nonlinear MPC methods.
Talk 2:
Title:
Good or Bad -- When is plant nonlinearity an obstacle for control?
Abstract:
Virtually every real technical process to be controlled is nonlinear in nature. Nevertheless, linear system analysis and linear controller design methods have proven to be adequate in many control applications. On the other hand, there are nonlinear systems that require or benefit from nonlinear control. Therefore, recognizing a system as being nonlinear does not suffice, but theextent and severity of a system's inherent nonlinearity is the crucial characteristic in order to decide whether linear system analysis and controller synthesis methods are adequate or whether nonlinear methods are needed. The introduction of so-called nonlinearity measures is an attempt to systematically approach this problem. In this talk, we review existing approaches to nonlinearity assessment, state the most important results and give a glance ahead of what might be expected from this field in future.
Talk 3 (modified version of my CDC 2006 semi-plenary):
Title:
The Continuing Joy of Dissipation Inequalities
Abstract:
Dissipation inequalities play a fundamental role in systems and control theory and dissipativity is a very useful concept in the analysis and design of nonlinear control systems. The idea of dissipativity was introduced in the early 1970s as a generalization of Lyapunov inequalities to systems having inputs and outputs. While Lyapunov functions serve to show the stability of dynamical systems, dissipation inequalities can be applied more widely depending on the choice of the so-called supply rate. Classical cases being for example the well-known passivity or the $L_2$-norm characterization of nonlinear systems. Like in Lyapunov theory the biggest problem in applications is the construction of a storage function, which is the generalization of the Lyapunov function. However for the important class of polynominal systems, i.e. systems with polynomial nonlinearities, recent advances in the area of computational semialgebraic geometry, namely semidefinite programming and the sum of squares decomposition, allow a reliable and efficient solution in many cases.
In this talk we will give a brief historical perspective and an introduction to the system theoretic concept of dissipation inequalities. We will present exemplary recent results on the stability analysis of nonlinear differential algebraic equation systems, minimum phase analysis, and nonlinear feedback and observer design that are based on novel dissipation inequalities and will discuss questions concerning the computation of the storage functions. The methods will be demonstrated and critically assessed with various examples from engineering and systems biology.
Talk 4:
Title:
Systems Biology: How Can Control Engineers Help to Understand
Biology?
Abstract:
During the last decade, biology has faced a technological revolution with the development of high-throughput methods for the characterization of the genome, transcriptome and proteome and has given rise to an unprecedented amount of biological data. For the first time in history this data allows for a systematic mathematical modeling of a huge class of biological processes and phenomena with one of the goals being to complement in vivo experiments by computer simulations.
In this talk the role of systems theory and control for the development of the new field of systems biology will be discussed. In particular we will argue that the role of the systems sciences is not restricted to supporting the mathematical modeling process, but that systems theoretic investigations will play an important role for developing a better understanding of life. Conversely, the field of systems and control can also learn greatly from the way nature solves regulation problems in its highly complex networks. It can be expected that in the future systems biology will stimulate the development of new control paradigms inspired by nature.
Top of the page
Joao Hespanha, University of California Santa Barbara
João P. Hespanha received the Licenciatura in electrical and computer engineering from the Instituto Superior Técnico, Lisbon, Portugal in 1991 and the M.S. and Ph.D. degrees in electrical engineering and applied science from Yale University, New Haven, Connecticut in 1994 and 1998, respectively. He currently holds a Professor position with the Department of Electrical and Computer Engineering, the University of California, Santa Barbara. From 1999 to 2001, he was an Assistant Professor at the University of Southern California, Los Angeles. Dr. Hespanha is the associate director for the Center for Control, Dynamical-systems, and Computation (CCDC) and an executive committee member for the Institute for Collaborative Biotechnologies (ICB), an Army sponsored University Affiliated Research Center (UARC). His research interests include hybrid and switched systems; the modeling and control of communication networks; distributed control over communication networks (also known as networked control systems); the use of vision in feedback control; stochastic modeling in biology; and game theory. He is the author of over one hundred technical papers and the PI and co-PI in several federally funded projects. Dr. Hespanha is the recipient of the Yale University's Henry Prentiss Becton Graduate Prize for exceptional achievement in research in Engineering and Applied Science, a National Science Foundation CAREER Award, the 2005 best paper award at the 2nd Int. Conf. on Intelligent Sensing and Information Processing, the 2005 Automatica Theory/Methodology best paper prize, and the 2006 George S. Axelby Outstanding Paper Award. Since 2003, he has been an Associate Editor of the IEEE Transactions on Automatic Control.
More information about Dr. Hespanha's research can be found at http://www.ece.ucsb.edu/~hespanha
LECTURES
1) Switched Systems: Mixing Logic with Differential Equations
As computers, digital networks, and embedded systems become ubiquitous and increasingly complex, one needs to understand the coupling between logic-based components and continuous physical systems. This prompted a shift in the standard control paradigm-in which dynamical systems were typically described by differential or difference equations-to allow the modeling, analysis, and design of systems that combine continuous dynamics with discrete logic. This new paradigm is often called hybrid or switched control.
This talk deals precisely with systems that result from the interconnection of differential equations with logic-based decision rules. Such systems are hybrid in the sense that some of the variables that describe their behavior take continuous values (e.g., the state of a differential equation) whereas others take discrete values (e.g., a Boolean value, or the state of a finite automaton). We are particularly interested in switched system. These are systems for which the continuous dynamics are effectively determined by the values of one or more discrete variables.
In the talk, we present several mathematical tools that have been developed to understand the behavior of switched systems. These tools are introduced in the context of specific applications where both logic and differential equations arise naturally. We draw these examples from areas as diverse as computer networks, vision-based robotics, and adaptive control. The goal of this talk is twofold: (i) demonstrate that switched systems are ubiquitous and of significant practical application, and (ii) show that a unified theory of switched systems is becoming available.
2) Stochastic hybrid models in biology: Modeling and analysis
The time evolution of chemically reacting molecules is sometimes modeled using a stochastic formulation, which takes into account the inherent randomness of molecular motion. This formulation is especially useful for complex reactions inside living cells, where small populations of key reactants can set the stage for significant stochastic effects. In this talk, we show how Stochastic Hybrid Systems can be used to construct stochastic models for chemical reactions.
Hybrid systems combine continuous-time dynamics with discrete modes of operation. The states of such system usually have two distinct components: one that evolves continuously, typically according to a differential equation; and another one that only changes through instantaneous jumps. To model chemical reactions, we actually need Stochastic Hybrid Systems (SHSs) where transitions between discrete modes are triggered by stochastic events, much like transitions between states of a continuous-time Markov chains. However, the rate at which transitions occur is allowed to depend on both the continuous and the discrete states of the SHS.
Several tools are available to analyze SHSs. Among these, we discuss the use of the extended generator, infinite-dimensional moment dynamics, and finite-dimensional truncations by moment closure. The application of these tools is illustrated in the context of modeling the evolution of populations of molecules undergoing a system of chemical reactions.
3) Communication constraints in networked control systems
Networked Control Systems (NCSs) are spatially distributed systems for which the communication between processes, sensors, actuators, and/or controllers is supported by a digital communication network. This type of systems exhibits several characteristics that make them unique from a control perspective.
In this talk we address the effect of limited communication bandwidth and network latency in the overall performance of a closed-loop NCS. Not surprisingly, there is a trade-off between the amount of communication resources utilized and the control performance achievable. For prototypical examples (linear processes and quadratic costs) we construct optimal communication logics that achieve optimal performance with minimal communication. The effect of network latency is also investigated in this context.
Top of the page
Stephane Lafortune University of Michigan
Stephane Lafortune received the B. Eng degree from Ecole Polytechnique de Montreal in 1980, the M. Eng. degree from McGill University in 1982, and the Ph.D. degree from the University of California at Berkeley in 1986, all in electrical engineering. Since September 1986, he has been with the University of Michigan, Ann Arbor, where he is a Professor of Electrical Engineering and Computer Science. He served as Associate Chair of the EECS Department in the period 2000-2003. Dr. Lafortune is a Fellow of the IEEE (1999) for "contributions to the theory of discrete event systems". He received the Presidential Young Investigator Award from the National Science Foundation in 1990 and the George S. Axelby Outstanding Paper Award from the Control Systems Society of the IEEE in 1994 (for a paper co-authored with S. L. Chung and F. Lin) and in 2001 (for a paper co-authored with G. Barrett). His current research interests are in discrete event systems and communication networks. He has also performed research in the area of intelligent transportation systems. He co-authored, with C. Cassandras, the textbook "Introduction to Discrete Event Systems" (Kluwer Academic Publishers, 1999). A second edition of this textbook is to be published by Springer in 2007. The web site www.eecs.umich.edu/umdes may be consulted for further information.
Proposed talk 1:
Title: "Monitoring and Diagnosis of Discrete Event Systems"
Abstract:
We are interested in the detection of "significant" events, such as faults, in technological systems whose dynamics are modeled in the framework of discrete event systems. Discrete event systems are dynamic systems with discrete state spaces and event-driven dynamics. They occur in the study of many classes of systems in automated manufacturing, communication networks, and process control, for example, where communication, computing, and sensor technologies are rapidly evolving.
In the first part of the talk, we will review the salient features of a methodology for fault diagnosis of discrete event sytems termed the "Diagnoser Approach". This approach has been successfully used in several domains, incuding document processing systems and intelligent transportation systems. In the second part of the talk, we will present some recent extensions of this methodology regarding the ability to distribute the diagnosis function among a set of diagnoser modules in the case of large systems composed of several interconnected components.
Proposed talk 2:
Title: "Decentralized and Distributed Control of Partially-Observed Discrete Event Systems"
Abstract:
This talk will present a critical overview of key results on the control of partially-observed distributed discrete event systems. The control framework adopted is that of the theory of supervisory control, initiated by Ramadge & Wonham in the 1980's. Both decentralized and distributed control architectures will be considered. In decentralized architectures, a set of local supervisors work jointly to enforce a global specification on the controlled behavior; these supervisors have different information structures and do not communicate in real-time, hence the adjective "decentralized". The state-of-the art in decentralized control will be reviewed with focus on the role of inference and on the curse of undecidability. In "distributed" architectures, the supervisors are allowed to exchange information in real-time, leading to what are called networked systems. In several classes of networked systems, energy, bandwidth, and/or security often require to minimize communications among supervisors. The intricacies of the synthesis of minimum communication policies will be illustrated. Recent results on this topic will be presented.
Top of the page
Li Qiu Hong Kong University of Science and Technology
Li Qiu received the B.Eng degree from Hunan University, Changsha, Hunan, China, in 1981, and the M.A.Sc. and Ph.D. degrees from the University of Toronto, Toronto, Ont., Canada, in 1987 and 1990, respectively, all in electrical engineering. He worked briefly at University of Toronto, Canadian Space Agency, University of Waterloo, and University of Minnesota before joining Hong Kong University of Science and Technology, Hong Kong SAR, China, in 1993, where he is now a professor of Electronic and Computer Engineering. He has also held visiting positions at Zhejiang University, Australian Defense Force Academy, and Harbin Institute of Technology.
Prof. Qiu's research interests include system, control, information theory, and mathematics for information technology. He received the Best Theoretical Paper Award in the 5th World Congress on Intelligent Control and Automation. He coauthored together with Kemin Zhou an undergraduate textbook \Introduction to Feedback Control" which is to be published by Prentice-Hall in 2007. He served as an associate editor of the IEEE Transactions on Automatic Control and an associate editor of Automatica. He is now an associate editor of Journal of Control Theory and Applications and a member of the editorial board of the International Journal of Control. He is the general chair of the 7th Asian Control Conference, which is to be held in Hong Kong in 2009. He is a fellow of IEEE.
LECTURES
TALK 1. From Singular Values to Canonical Angles
In matrix analysis, singular values play important roles. They not only are the subject of a rich and elegant theory, but also have wide applications in countless technical disciplines. Up to now, the theory of singular values has more or less matured, but the domain of applications is still expanding.
Recently, quite a few technical problems in system and information theory call for the analysis in the set of linear subspaces. The set of all linear subspaces of a given dimension of an ambient linear space is called a Grassmannian or a Grassmann manifold. In linear subspace analysis, the roles of singular values are replaced by canonical angles. The concepts of singular values and canonical angles are like twins. They were born in nearly the same time, share a large number of similar properties, and have matching theoretical and application importance. However, the growth of the latter is much slower than the former. This reminds us Schwarzenegger and De Vito in the American movie "Twins".
In this lecture, we present the history, theory, and applications of singular values and canonical angles in a parallel way and examine the connections of the two sets of numbers. The singular values serve as reviews and motivations. The emphasis is on canonical angles, especially on some recent theoretical advances and application case studies. We will also speculate more possible applications of canonical angles based on the track record of the singular values.
TALK 2. Fundamental Performance Limitations in Feedback Control
The past 30 years have seen remarkably rapid progress in the system control theory based on optimization techniques. The theory, apart from its theoretic elegance, has been shown to be effective in various applications. However, the solutions of the optimization problems, in most cases in terms of numerical algorithms, do not provide a clear picture of the relationship between the optimal performance of the controlled system and the characteristics of the plant to be controlled, nor do they provide a clear idea of the effect of the changes in the plant parameters, the allocation of the actuators and sensors, the choice of the control structures, and the information constraints in the feedback channel on the optimal performance obtainable.
On the other hand, the history of control practice has generated some empirical understanding of the difficulty in feedback control given in terms of rules-of-thumb, such as that nonminimum phase systems are hard to control and that close unstable poles to nonminimum phase zeros add additional difficulty to control. The efforts to quantify these rules-of-thumb and to find the exact mathematical relationship between simple plant characteristics and achievable performance in feedback control have formed a research area in itself. Many interesting results have been obtained to explain the various design limitations and tradeoffs in multivariable feedback control.
In this lecture, we plan to give a systematic coverage of the available results on the fundamental limitations in feedback control and also to propose some new research issues in this rapidly developing area.
TALK 3. Pre-Classical Tools for Post-Modern Control
The dissemination and the application of the modern and post-modern control theory have been hindered by the popular myth that its understanding requires advanced mathematical background.
In this lecture we present a systematic optimal and robust control theory for single-input single-output (SISO) systems in a language suitable for undergraduate teaching. The theory is based on the post-modern philosophy, emphasizing analyticity, optimality, robustness, CAD suitability, and rigor, but uses pre-classical tools not much beyond the Routh stability criterion and polynomial Diophantine equations. The theory covers many post-modern control topics, including the computation of the energy (2-norm) of a signal or a system, the computation of the resonance peak (infinity-norm) of a system, optimal transient stabilization (LQG control), and optimal robust stabilization with respect to the Vinnicombe metric (H_infinity control). The analysis theory is mainly based on a Routh-like table and the synthesis theory relies mainly on solutions to polynomial Diophantine equations. Making such a theory available facilitates the teaching and application of advanced optimal and robust control of SISO systems, described by transfer functions, using mostly polynomial arithmetic understandable by students and engineers with minimal mathematical sophistication. This endeavor may change the common perception that the classical theory is associated with trial-and-error designs and approximate reasoning, while at the same time can demystify post-modern control theory and the advanced mathematics associated with it. It is our belief that the teaching materials in the elementary level should be better connected with the most recent developments in control theory and that one of the main reasons for the widening gap between control theory and control practice is the widening gap between theoretical development and education.
Top of the page
Jie Huang Chinese University of Hong Kong
Department of Automation and Computer-aided Engineering
Jie Huang got his diploma from Fuzhou University, China in 1980, Master degree from Nanjing University of Science and Technology, China in 1982, and completed his Ph.D. degree at Johns Hopkins University in 1990. He was a postdoctoral fellow at Johns Hopkins University from September 1990 to July 1991. From August 1991 to August 1995, he worked in industry in USA. He joined the Chinese University of Hong Kong in 1995 as an Associate Professor in Department of Automation and Computer-aided Engineering, and is now a professor. He is also the Director of The Applied Control and Computing Laboratory there. He also holds a professorship with South China University of Technology sponsored by Cheung Kong Scholars Award Program. He has been a science advisor of The Leisure and Cultural Services Department of HKSAR, and honorary advisor of the Science Museum of Hong Kong. His research interests include nonlinear control theory and applications, industrial control and automation, neural networks, computer-aided control system design, and guidance and control of flight vehicles (aircraft, missile, and spacecraft). His research has led to publications of over 140 papers in international journals and conference proceedings, and a monograph "Nonlinear output regulation: Theory and Applications", SIAM, 2004. Dr. Huang is a Fellow of IEEE, a member of Editorial Board of Communications in Information and Systems, and Associate Editor of Control Theory and Applications. He was Associate Editor of Asian Journal of Control from 1999-2002, and Associate Editor of IEEE Transactions on Automatic Control from 2002 to 2004. He has been the Guest Editor for International Journal of Robust and Nonlinear Control, and Asian Journal of Control. He is the General Chair of 2002 International Conference on Control and Automation, and Publicity Chair of 41st IEEE Conference on Decision and Control. He has been plenary speaker in several international conferences or symposiums. He has organized several invited sessions at various International Conferences including American Control Conferences and IEEE Conference on Decision and Control. He was the co-organizer and lecturer of the workshop Output Regulation in Nonlinear Systems at 1999 IEEE Conference on Decision and Control.
LECTURES
TALK 1.
Title : Nonlinear Output Regulation: Theory and Applications
Output regulation problem, or alternatively, servomechanism problem, aims to achieve, in addition to closed-loop stability, asymptotic tracking and disturbance rejection in an uncertain system. Thus it poses a more challenging problem than stabilization. Output regulation problem is a general mathematical formulation of many control problems encountered in our daily life including the landing and taking-off of aircraft, attitude control of spacecraft, speed regulation of motors and so forth. This lecture will focus on the robust output regulation problem for nonlinear systems, which has been one of the central problems in control theory since the 1990s. The talk will start from an introduction to the problem of output regulation, and then proceed to highlight the establishment of a general framework that can cast the robust output regulation problem for a given plant into the robust stabilization problem of an augmented plant, thus setting the stage for systematically tackling output regulation with various stability requirements. The theoretical results will be illustrated with applications to some benchmark nonlinear systems. The talk will be closed with some remarks on open issues.
Top of the page
Bassam Bamieh
Bassam Bamieh received his Electrical Engineering and Physics degree from Valparaiso University in 1983, and his M.Sc. and PhD degrees from Rice University in 1986 and 1992 respectively. During 1991-98 he was with the department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign. He is currently a Professor in the Mechanical Engineering department at the University of California at Santa Barbara which he joined in 1998. His current research interests are in distributed systems, shear flow turbulence modeling and control, quantum control, micro-cantilevers modeling and control, and optical actuation via optical tweezers. He is a past receipient of the AACC Hugo Schuck best paper award, the IEEE CSS Axelby outstanding paper award, an NSF CAREER award, and is currently an associate editor of Systems and Control Letters.
LECTURES
会员活动 
