IEEE CSS Distinguished Lectures Hosted by the Chapter in 2008
Funded by the IEEE Control Systems Society
(CSS), the CSS Distinguished Lecture Series is primarily set up to help Society
chapters provide interesting and informative programs for the membership, but
the Series may also be of interest to industry, universities, and other
parties. The IEEE Singapore Control Systems Chapter features the following
distinguished lectures by Professor Li Qiu of the Hong Kong University of
Science and Technology on September 19, 2008, and by Professor Iven Mareels of
Speaker of the 2nd IEEE CSS Distinguished Lecture in 2008 (October 28, 2008)
Professor Iven Mareels was born in
The Lecture: Control Theory Meets Neuroscience
From its very onset cybernetics was interested in communication and control as it is implemented in either engineered systems or biology. Indeed much of the seminal work of Norbert Wiener, John Von Neumann and Claude Shannon was motivated by the fact that their theories and insight would lead to elucidating how the mind works.
This section reviews some of the basic questions they were interested in, like memory capacity and computational capacity of the brain, and compare some of their predictions with measurements and neuroscience estimates that have been made more recently.
Of particular interest to systems theory people is the fact that in order to elucidate how learning works, especially in motor control, neuroscience researchers are particularly interested in motor control in interactions with the environment that are described as “unstable”, like drilling or writing or standing/walking. Indeed in view of recent advances in our understanding of feedback entropy and invariance entropy, control theory can shed light on the minimum required feedback information rate that is necessary for a stable feedback loop to exist, and may settle the question on whether or not a feedback loop exists. The latter is of great interest, for example the “simple” question, “Do humans use feedback during walking?” is still considered an open question.
The notion of feedback entropy is presented, and illustrated for both linear and nonlinear feedback systems. It is applied to an experimental model of gross motor for writing and walking. This leads to a lower bound estimate of the bit rate capacity of the typical neural circuits that support gross motor movement.
Speaker of the 1st IEEE CSS Distinguished Lecture in 2008 (September 19, 2008)
Professor Li Qiu received the B.Eng. degree from
Professor Qiu’s research interests include system, control,
information theory, and mathematics for information technology. He served as an
associate editor of the IEEE
Transactions on Automatic Control and
an associate editor of Automatica. He is now a Distinguished Lecturer of IEEE Control
Systems Society and the general chair of the 7th Asian Control Conference,
which is to be held in
The Lecture: Measure of Instability and Multivariable Networked Stabilization with Channel Resource Allocation
In this talk, we will survey the history of an instability measure of an LTI system and its connections with various feedback control problem. Then we will present its connections to networked control problems of multivariable systems. In such problems, communication resource allocation among various signal transmission channels becomes a design issue in addition to the usual controller design.
We will see that some optimal and robust control problems arising in networked control are nontraditional and highly nonconvex but can be nicely and analytically solved, and the solutions are given in terms of the instability measure.
The results to be reported are the recent findings in the joint research with Professor Guoxiang Gu of LSU.
IEEE CSS Distinguished Lectures Hosted by the Chapter in 2007
Speaker of the 2nd IEEE CSS Distinguished Lecture in 2007 (May 17, 2007)
Professor Carlos E. de Souza was born in João Pessoa,
Brazil. He received the B.E. degree in
Electrical Engineering from the Federal University of Pernambuco,
Brazil, in 1976 and the doctoral degree from the University Pierre & Marie
The Lecture: Robust State Estimation for Uncertain Dynamical Systems
One of the fundamental problems in control systems is the estimation of the state variables of a dynamic system using available noisy measurements. Estimation methods in the minimum variance sense, i.e. the celebrated Kalman filtering, and in the minimax sense, i.e. H-infinity filtering, have been developed in the past decades. These methods rely on the knowledge of a perfect dynamic model for the signal generating system in order to provide a guaranteed performance. In many cases, however, only an approximate model of the system is available and, in such situations, these methods can fail to provide an acceptable performance. This lecture is concerned with the problem of robust state estimation for dynamic systems subject to parameter uncertainty in the system state-space model. First, the filtering problem and traditional filter designs will be reviewed. Then, design methods of robust filters with an optimized guaranteed performance, in spite of large parameter uncertainty, will be discussed.
Speaker of the 1st IEEE CSS Distinguished Lecture in 2007 (March 13, 2007)
Professor Thomas Parisini was born in
involved in the organization and in the technical program committees of several
IEEE CSS sponsored conferences including the IEEE Conf. on Decision and Control
and the IEEE Conf. on Control Applications. In particular, he was Vice-Program
Chair of the 2003 IEEE Conf. on Decision and Control, 2003, the Program Chair
of the IEEE Int. Symp. on
Intelligent Control, held in
The Lecture: Fault Diagnosis of Nonlinear Uncertain Systems: an Adaptive Learning Approach
The objective of this lecture is give a tutorial and detailed overview of a recent approach to the solution of the challenging problem of fault detection and isolation and of a class of nonlinear uncertain systems. This methodology is based on the design of a monitoring module that provides the information about the detection of a fault and the information about the specific fault that occurred in a class of a priori-specified fault structures. This module is made of a bank of nonlinear adaptive estimators. One of the nonlinear adaptive estimators is the fault detection and approximation estimator (FDAE) used for detecting and approximating faults. An on--line approximation model, typically based on neural approximators, is used in the FDAE. The remaining ones are fault isolation estimators (FIEs) used only after a fault is detected for isolation purposes. Each FIE corresponds to a particular type of fault in pre-secified class. Under normal operating conditions (without faults), the FDAE is the only one monitoring the system. Once a fault is detected, then the bank of FIEs is activated and the FDAE goes into the mode of approximating the fault function. The case that none of the isolation estimators matches the occurred fault (to some reasonable degree) corresponds to the occurrence of a new and unknown type of fault, and the approximated fault model can then be used to update the fault class and also the bank of isolation estimators. The fault model generated either by the isolation estimators (in the case of a match) or the detection/approximation estimator is used for fault diagnosis and provides the information to be used by the controller module for fault accommodation. In the lecture, a complete analysis of the above scheme will be carried out in a tutorial but rigorous way and some simulation examples will be also reported, showing the practical aspects involved in the use of this recent approach to control of nonlinear uncertain systems in presence of the possible occurrence of faults and malfunctions.
IEEE CSS Distinguished Lectures Hosted by the Chapter in 2005
Speaker of the 2nd IEEE CSS Distinguished Lecture in 2005 (October 14, 2005)
Professor Jie Huang
obtained his Ph.D. degree at
Dr. Huang is an Editor at Large of Communications in Information and Systems, a Subject Editor of International Journal of Robust and Nonlinear Control, and Associate Editor of Journal 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, Asian Journal of Control, and IEEE Transactions on Neural Networks.
Dr. Huang is a Fellow of IEEE, and an IEEE Control System Society Distinguished Lecturer.
The Lecture: Nonlinear Output Regulation: Theory and Applications
Venue: Department of Electrical & Computer Engineering,
October 14, 2005
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, orbiting of satellites, speed regulation of motors and so forth. This talk 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.
Speaker of the 1st IEEE CSS Distinguished Lecture in 2005 (June 13 & 14, 2005)
Mareels was born in
He is Fellow of the
Since 1996, he is a co-editor in chief, together with Prof. A. Antoulas for the international Journal Systems & Control Letters.
Iven Mareels received the Vice-Chancellor's Award for
Excellence in Teaching in 1994 from the
Lecture 1: Information Theory and Feedback
In this lecture, we address the question of stabilising an open loop unstable system through a data rate limited communication channel. It turns out that there is a fundamental limit, even when the communication channel is error free. There is a minimum data rate required to be able to stabilize an unstable system, and above which a stabilising feedback law can be constructed.
We review the ideas first in the context of linear systems subject to additive white Gaussian noise in the state transition map and the observation map, where the required data rate is expressed in terms of the unstable eigenvalues of the state transition map. Subsequently we pose the same question in a nonlinear setting. To this end we first define the concept of topological feedback entropy, which is an open-loop system property. It turns out that the minimum required data rate for stabilization is precisely the plant's topological feedback entropy.
Finally we address the issue in the context of a network of dynamically interconnected systems. To illustrate the power of the result we compute the minimum data rate required in the human nervous system to complete the task of walking.
This lecture reports on joint work with Dr. Girish Nair, Prof. R. Evans and Prof. W. Moran.
Lecture 2: Signal Processing and Control Theory in Support of Brain Research
The human brain is the subject to immense research effort around the world. From a medical perspective, the need is pressing, as witnessed by the following widely reported figures (2000 world health data):
This lecture provides an overview of the interdisciplinary research the presenter has engaged in over the last two years. It summarises his interaction with researchers from neuro science, psychiatry and physiology and will hopefully encourage others with a background in signal processing and control theory to contribute to the global brain research efforts. The talk focuses on the research questions.
New and old measurement techniques are promising a wealth of new data requiring new and automated techniques for interpretation, and computer assisted diagnostics. We consider two general measurement techniques: magnetic resonance imaging and eeg and review a number of research questions that are in particular enabled by control and/or system theoretic ideas: