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SYSID 2009 - Semi-Plenary Lectures
Michel Fliess
Model-free control and intelligent PID controllers: towards a possible trivialization of nonlinear control ?
Michel Fliess is a Research
Director at the Centre National de
la Recherche Scientifique and works at the École Polytechnique
(Palaiseau,
France).
He is the Head of the INRIA project called ALIEN, which is devoted to the study and the development of new techniques in identification and estimation.
In 1991, he invented with J. Lévine, P. Martin and P. Rouchon, the notion of "differentially flat'' systems which is playing a major role in control applications.
He is the Head of the INRIA project called ALIEN, which is devoted to the study and the development of new techniques in identification and estimation.
In 1991, he invented with J. Lévine, P. Martin and P. Rouchon, the notion of "differentially flat'' systems which is playing a major role in control applications.
Tryphon Georgiu
Geometric concepts and models in power spectral analysis
Tryphon T. Georgiou received the
Diploma in Mechanical and Electrical
Engineering from the National Technical University of Athens, Greece,
in 1979, and the Ph.D. degree from the University of Florida,
Gainesville, in 1983. He served on the faculty of Florida Atlantic
University and of Iowa State University prior to joining the University
of Minnesota, in 1989, where he is now a Professor of Electrical and
Computer Engineering, a co-director of the Control Science and
Dynamical Systems Center, and holds the Vincentine Hermes-Luh Chair.
Dr. Georgiou has served as an elected member of the Board of Governors of the Control Systems Society, and as an Associate Editor for the IEEE Transactions on Automatic Control, the IEEE Transactions on Signal Processing, the SIAM Journal on Control and Optimization, and the Systems and Control Letters.
Dr. Georgiou is a Fellow of the IEEE and a co-recipient of the George Axelby Outstanding Paper award of the IEEE Control Systems Society for the years 1992 and 1999, for joint works with Malcolm C. Smith (University of Cambridge), and for 2003, for joint work with Chris I. Byrnes (Washington University, St. Louis) and Anders Lindquist (KTH, Stockholm).
Dr. Georgiou's research interests lie in the general area of control engineering, systems, information theory, and applied mathematics.
Dr. Georgiou has served as an elected member of the Board of Governors of the Control Systems Society, and as an Associate Editor for the IEEE Transactions on Automatic Control, the IEEE Transactions on Signal Processing, the SIAM Journal on Control and Optimization, and the Systems and Control Letters.
Dr. Georgiou is a Fellow of the IEEE and a co-recipient of the George Axelby Outstanding Paper award of the IEEE Control Systems Society for the years 1992 and 1999, for joint works with Malcolm C. Smith (University of Cambridge), and for 2003, for joint work with Chris I. Byrnes (Washington University, St. Louis) and Anders Lindquist (KTH, Stockholm).
Dr. Georgiou's research interests lie in the general area of control engineering, systems, information theory, and applied mathematics.
Mustafa Khammash
Stochastic gene expression: modeling, analysis, and identification
Mustafa Khammash is the Director
of the Center for Control, Dynamical
systems, and Computations (CCDC) at the University of California at
Santa Barbara (UCSB). He also holds a Professor appointment in the
Mechanical Engineering at UCSB. He received his B.S. degree from Texas
A&M University in 1986 and his Ph.D. from Rice University in 1990,
both in electrical engineering. In 1990, he joined the Electrical
Engineering Department at Iowa State University where he created and
led the dynamics and control program. In 2001, was a visiting Professor
at Caltech, and in 2002 he joined the faculty of the department of
Mechanical Engineering at UCSB.
Mustafa Khammash’s research contributions are in the area of control theory and its applications to engineering and to biological systems. His theoretical work lies in the area of robustness analysis and synthesis of interconnected dynamic systems, where he has developed methodology for the analysis and design of robust control systems under persistent disturbances and model uncertainty. His work also focuses on using control theory for the quantitative analysis of networks of dynamically interacting biological components, with the goal of reverse engineering these networks to understand how they robustly achieve biological function. He is currently developing computational methods for the analysis of stochastic dynamics and their applications in the area of Systems Biology.
Mustafa Khammash is a Fellow of the IEEE. He is the recipient of the National Science Foundation Young Investigator Award, the Japan Society for the Promotion of Science (JSPS) Fellowship, the Iowa State University Foundation Early Achievement in Research and Scholarship Award, the ISU College of Engineering Young Faculty Research Award, and the Ralph Budd Best Engineering PhD Thesis Award.
Mustafa Khammash’s research contributions are in the area of control theory and its applications to engineering and to biological systems. His theoretical work lies in the area of robustness analysis and synthesis of interconnected dynamic systems, where he has developed methodology for the analysis and design of robust control systems under persistent disturbances and model uncertainty. His work also focuses on using control theory for the quantitative analysis of networks of dynamically interacting biological components, with the goal of reverse engineering these networks to understand how they robustly achieve biological function. He is currently developing computational methods for the analysis of stochastic dynamics and their applications in the area of Systems Biology.
Mustafa Khammash is a Fellow of the IEEE. He is the recipient of the National Science Foundation Young Investigator Award, the Japan Society for the Promotion of Science (JSPS) Fellowship, the Iowa State University Foundation Early Achievement in Research and Scholarship Award, the ISU College of Engineering Young Faculty Research Award, and the Ralph Budd Best Engineering PhD Thesis Award.
Mario Milanese
Set membership methods for identification, prediction and filtering of nonlinear systems
Mario Milanese graduated in
electronic engineering at Politecnico
di Torino, Torino, Italy, in 1967. From 1968 he was assistant professor
at Politecnico di Torino and from 1972 accociate professor at the
University of Torino. Since 1980, he
has been a full professor of system theory at Politecnico
di Torino. From 1982 to 1987, he was head of the Dipartimento
di Automatica e Informatica at the Politecnico di
Torino.
His research interests include identification, prediction, filtering and control of complex systems with applications to biomedical, automotive, aerospace, financial, environmental, and energy problems. He is the author of more than 250 papers on these topics in international journals and conference proceedings. He is Co-Editor of the books "Robustness in Identification and Control", Plenum Press, 1989 and "Bounding Approaches to System Identification", Plenum Press, 1996.
He is inventor of 5 patents on the control of semiactive suspensions and on the control of tethered airfoils for wind energy generation. He has been responsible of several projects with industrial companies and european and national organizations on modeling and control in automotive, aerospace, biomedical and renewable energy fields. He has been recipient of the International Huspy Awards for Artificial Intelligence in Medicine, 1984 and of the Japan Society for the Promotion of Sciences, 1999.
His research interests include identification, prediction, filtering and control of complex systems with applications to biomedical, automotive, aerospace, financial, environmental, and energy problems. He is the author of more than 250 papers on these topics in international journals and conference proceedings. He is Co-Editor of the books "Robustness in Identification and Control", Plenum Press, 1989 and "Bounding Approaches to System Identification", Plenum Press, 1996.
He is inventor of 5 patents on the control of semiactive suspensions and on the control of tethered airfoils for wind energy generation. He has been responsible of several projects with industrial companies and european and national organizations on modeling and control in automotive, aerospace, biomedical and renewable energy fields. He has been recipient of the International Huspy Awards for Artificial Intelligence in Medicine, 1984 and of the Japan Society for the Promotion of Sciences, 1999.
Ralf Peeters
Johan Suykens
Support vector machines and kernel-based learning for dynamical systems modelling
Johan A.K. Suykens was born in
Willebroek Belgium in 1966. He received
the MSc degree in Electro-Mechanical Engineering and the PhD degree in
Applied Sciences from the Katholieke Universiteit Leuven, in 1989 and
1995, respectively. He is currently a Professor with K.U. Leuven in the
research group ESAT-SCD, which is active in the broad area of
mathematical engineering.
He is author of the books "Artificial Neural Networks for Modelling and Control of Non-linear Systems" (Kluwer Academic Publishers) and "Least Squares Support Vector Machines" (World Scientific), and editor of the books "Nonlinear Modeling: Advanced Black-Box Techniques" (Kluwer Academic Publishers) and "Advances in Learning Theory: Methods, Models and Applications" (IOS Press). He has served as associate editor for the IEEE Transactions on Circuits and Systems and since 1998 he is serving as associate editor for the IEEE Transactions on Neural Networks. He is a recipient of the IEEE Signal Processing Society 1999 Best Paper (Senior) Award and the International Neural Networks Society INNS 2000 Young Investigator Award.
In the last decade together with his research team, he focused on studying methods of support vector machines and kernel-based learning, in relation to different areas as system identification and control, neural networks and machine learning, mathematics and statistics, pattern recognition, optimization and others.
He is author of the books "Artificial Neural Networks for Modelling and Control of Non-linear Systems" (Kluwer Academic Publishers) and "Least Squares Support Vector Machines" (World Scientific), and editor of the books "Nonlinear Modeling: Advanced Black-Box Techniques" (Kluwer Academic Publishers) and "Advances in Learning Theory: Methods, Models and Applications" (IOS Press). He has served as associate editor for the IEEE Transactions on Circuits and Systems and since 1998 he is serving as associate editor for the IEEE Transactions on Neural Networks. He is a recipient of the IEEE Signal Processing Society 1999 Best Paper (Senior) Award and the International Neural Networks Society INNS 2000 Young Investigator Award.
In the last decade together with his research team, he focused on studying methods of support vector machines and kernel-based learning, in relation to different areas as system identification and control, neural networks and machine learning, mathematics and statistics, pattern recognition, optimization and others.