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Plenaries
Plenaries talks
Plenaries talks will be presented in plenary sessions. The confirmed plenary speakers include (in alphabetical order):
- Jean-Bernard Lasserre, LAAS-CNRS, Toulouse, France
- Maarten Steinbuch, Techical University of Eindhoven, The Netherlands
- Marios Polycarpou, University of Cyprus
- Yutaka Yamamoto, Kyoto University
PLENARY SPEAKERS AND TALKS
The confirmed plenary speakers are listed in alphabetical order.
Abstract:
In many problems in control, optimal and robust control, one has to solve global optimization problems of the form: P : f* = minx { f(x) : x ∈ K}, or, equivalently, f* = max{λ : f - λ ≥ 0 on K}, where f is a polynomial (or even a semi-algebraic function) and K is a basic semi-algebraic set. One may even need solve the "robust" version min{f(x) : x ∈ K; h(x; u) ≥ 0, ∀u ∈ U} where U is a set of parameters. For instance, some static output feedback problems can be cast as polynomial optimization problems whose feasible set K is de ned by a polynomial matrix inequality (PMI). And robust stability regions of linear systems can be modeled as parametrized polynomial matrix inequalities (PMIs) where parameters u account or uncertainties and (decision) variables x are the controller coefficients.
Therefore, to solve such problems one needs tractable characterizations of polynomials (and even semi-algebraic functions) which are nonnegative on a set, a topic of independent interest and of primary importance because it also has implications in many other areas.
We will review two kinds of tractable characterizations of polynomials which are non- negative on a basic closed semi-algebraic set K ⊂ Rn. The rst type of characterization is when knowledge on K is through its de ning polynomials, i.e., K = {x : gj(x) ≥ 0; j = 1, . . . ,m}, in which case some powerful certi cates of positivity can be stated in terms of some sums of squares (SOS)-weighted representation. For instance, this allows to de ne a hierarchy fo semide nite relaxations which yields a monotone sequence of lower bounds converging to f* (and in fact, nite convergence is generic). There is also another way of looking at nonnegativity where now knowledge on K is through moments of a measure whose support is K. In this case, checking whether a polynomial is nonnegative on K reduces to solving a sequence of generalized eigenvalue problems associated with a count- able (nested) family of real symmetric matrices of increasing size. When applied to P, this results in a monotone sequence of upper bounds converging to the global minimum, which complements the previous sequence of upper bounds. These two (dual) characterizations provide convex inner (resp. outer) approximations (by spectrahedra) of the convex cone of polynomials nonnegative on K.
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Abstract:
Advanced motion systems like pick-and-place machine used in the semiconductor industry, challenge the frontiers of systems and control theory and practice. In the design phase, control oriented design of the electro-mechanics is necessary in order to achieve the tight performance specifications. Once realized, and since experimentation is fast, a machine in the loop procedure can be explored to close the design loop from experiment, using experimental model building,model-based control design, implementation and performance evaluation. Extension of linear modelling techniques towards some classes of nonlinear systems is relevant for improved control of specific motion systems, such as with friction. In the application field of medical robotics the experiences from high tech motion systems can be used successfully, and an eye surgical robot with haptics will be shown as an example.
Biography:
Maarten Steinbuch is a full professor at Eindhoven University of Technology (TU/e), where he is head of the Control Systems Technology group of the Mechanical Engineering Department. He is also Director of the TU/e Automotive Systems Graduate Program and Scientific Director of the Centre of Competence for High Tech Systems of the Federation of Dutch Technical Universities. He has over 12 years of industrial experience with Philips Research Labs and Philips Center for Manufacturing Technology. He is Editor-in-Chief of the IFAC journal on Mechatronics and an Associate Editor of the International Journal of Powertrains. His research interests are in modeling and control of advanced motion systems, robotics for care and cure, automotive powertrains, and fusion plasmas.
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Abstract:
The emergence of networked embedded systems and sensor/actuator networks has given rise to advanced monitoring and control applications, where a large amount of sensor data is collected and processed in real-time in order to achieve smooth and efficient operation of the underlying system. The current trend is towards larger and larger sensor data sets, leading to so called big data environments. However, in situations where faults arise in one or more of the sensing devices, this may lead to a serious degradation in performance or even to an overall system failure. The goal of this presentation is to motivate the need for fault diagnosis in complex distributed dynamical systems and to provide a methodology for detecting and isolating multiple sensor faults in a class of nonlinear dynamical systems. The detection of faults in sensor groups is conducted using robust analytical redundancy relations, formulated by structured residuals and adaptive thresholds. Various estimation algorithms will be presented and illustrated, and directions for future research will be discussed.
Biography:
Marios M. Polycarpou is a Professor of Electrical and Computer Engineering and the Director of the KIOS Research Center for Intelligent Systems and Networks at the University of Cyprus. He received the B.A. degree in Computer Science and the B.Sc. degree in Electrical Engineering both from Rice University, Houston, TX, USA in 1987, and the M.S. and Ph.D. degrees in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 1989 and 1992 respectively. Prior to joining the University of Cyprus as founding Department Chair in 2001, he was Professor of Electrical and Computer Engineering and Computer Science at the University of Cincinnati, Ohio, USA. His teaching and research interests are in intelligent systems and control, fault diagnosis, computational intelligence, adaptive and cooperative control, and large-scale systems. Dr. Polycarpou has published over 230 papers in these areas and is the holder of 3 patents.
Prof. Polycarpou is a Fellow of the IEEE and currently serves as the President of the IEEE Computational Intelligence Society. He has served as the Editor-in-Chief of the IEEE Transactions on Neural Networks and Learning Systems from 2004 until 2010. He participated in more than 60 research projects/grants, funded by several agencies and industry in Europe and the United States. In 2011, Dr. Polycarpou was awarded the prestigious European Research Council (ERC) Advanced Grant.
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Abstract:
There has been remarkable progress in sampled-data control theory in the last two decades. The main achievement here is that there exists a digital (discrete-time) control law that takes the intersample behavior into account and makes the overall analog (continuous-time) performance optimal, in the sense of H-infinity norm. This naturally suggests its application to digital signal processing where the same hybrid nature of analog and digital is always prevalent. A crucial observation here is that the perfect band-limiting hypothesis, widely accepted in signal processing, is often inadequate for many practical situations. In practice, the original analog signals (sounds, images, etc.) are neither fully band-limited nor even close to be band-limited in the current processing standards.
The present talk describes how sampled-data control theory can be applied to reconstruct the lost high-frequency components beyond the so-called Nyquist frequency, and how this new method can surpass the existing signal processing paradigm. We will also review some concrete examples for sound processing, recovery of high frequency components for MP3/AAC compressed audio signals, and super resolution for image (still/moving) processing. We will also review some crucial steps in leading this technology to the commercial success of 40 million sound processing chips.
Biography:
Yutaka Yamamoto received his B. S. and M. S. degrees in engineering from Kyoto University, Kyoto, Japan, in 1972 and 1974, respectively, and the M. S. and Ph. D. degrees in mathematics from the University of Florida, in 1976 and 1978, respectively. He is currently a professor at the Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics of Kyoto University. His research and teaching interests are in realization and robust control of distributed parameter systems, learning control systems, and sampled-data systems, its application to digital signal processing, with emphasis on sound and image processing.
Dr. Yamamoto received the Sawaragi memorial paper award in 1985, outstanding paper award of SICE in 1987 and in 1997, the best author award of SICE in 1990 and in 2000, the George S. Axelby Outstanding Paper Award in 1996, and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Prizes for Science and Technology in 2007. He received the IEEE Control Systems Society Distinguished Member Award in 2009, and the Transition to Practice Award of the Control Systems Society in 2012, as well as the ISCIE Best Industrial Paper Award in 2009. He is a Fellow of the IEEE and SICE. He is currently President of the IEEE Control Systems Society. He has served as the Vice President for Technical Activities of the CSS for 2005-2006, and as Vice President for Publication Activities for 2007-2008. He was an associate editor of the IEEE Transactions on Automatic Control, Automatica, Systems and Control Letters, and is currently an associate editor of Mathematics of Control, Signals and Systems. He has served as a Senior Editor for the IEEE Transactions on Automatic Control for 2010-2011. He also served as an organizing committee member of the 35th CDC in 1996, MTNS '91 in Kobe, and as a member of program committees of several CDC's. He was the chair of the Steering Committee of MTNS, and served as General Chair of MTNS 2006. He is a past President of ISCIE of Japan.
The confirmed plenary speakers are listed in alphabetical order.
Abstract:
In many problems in control, optimal and robust control, one has to solve global optimization problems of the form: P : f* = minx { f(x) : x ∈ K}, or, equivalently, f* = max{λ : f - λ ≥ 0 on K}, where f is a polynomial (or even a semi-algebraic function) and K is a basic semi-algebraic set. One may even need solve the "robust" version min{f(x) : x ∈ K; h(x; u) ≥ 0, ∀u ∈ U} where U is a set of parameters. For instance, some static output feedback problems can be cast as polynomial optimization problems whose feasible set K is de ned by a polynomial matrix inequality (PMI). And robust stability regions of linear systems can be modeled as parametrized polynomial matrix inequalities (PMIs) where parameters u account or uncertainties and (decision) variables x are the controller coefficients.
Therefore, to solve such problems one needs tractable characterizations of polynomials (and even semi-algebraic functions) which are nonnegative on a set, a topic of independent interest and of primary importance because it also has implications in many other areas.
We will review two kinds of tractable characterizations of polynomials which are non- negative on a basic closed semi-algebraic set K ⊂ Rn. The rst type of characterization is when knowledge on K is through its de ning polynomials, i.e., K = {x : gj(x) ≥ 0; j = 1, . . . ,m}, in which case some powerful certi cates of positivity can be stated in terms of some sums of squares (SOS)-weighted representation. For instance, this allows to de ne a hierarchy fo semide nite relaxations which yields a monotone sequence of lower bounds converging to f* (and in fact, nite convergence is generic). There is also another way of looking at nonnegativity where now knowledge on K is through moments of a measure whose support is K. In this case, checking whether a polynomial is nonnegative on K reduces to solving a sequence of generalized eigenvalue problems associated with a count- able (nested) family of real symmetric matrices of increasing size. When applied to P, this results in a monotone sequence of upper bounds converging to the global minimum, which complements the previous sequence of upper bounds. These two (dual) characterizations provide convex inner (resp. outer) approximations (by spectrahedra) of the convex cone of polynomials nonnegative on K.
[back to top...]
Abstract:
Advanced motion systems like pick-and-place machine used in the semiconductor industry, challenge the frontiers of systems and control theory and practice. In the design phase, control oriented design of the electro-mechanics is necessary in order to achieve the tight performance specifications. Once realized, and since experimentation is fast, a machine in the loop procedure can be explored to close the design loop from experiment, using experimental model building,model-based control design, implementation and performance evaluation. Extension of linear modelling techniques towards some classes of nonlinear systems is relevant for improved control of specific motion systems, such as with friction. In the application field of medical robotics the experiences from high tech motion systems can be used successfully, and an eye surgical robot with haptics will be shown as an example.Biography:
Maarten Steinbuch is a full professor at Eindhoven University of Technology (TU/e), where he is head of the Control Systems Technology group of the Mechanical Engineering Department. He is also Director of the TU/e Automotive Systems Graduate Program and Scientific Director of the Centre of Competence for High Tech Systems of the Federation of Dutch Technical Universities. He has over 12 years of industrial experience with Philips Research Labs and Philips Center for Manufacturing Technology. He is Editor-in-Chief of the IFAC journal on Mechatronics and an Associate Editor of the International Journal of Powertrains. His research interests are in modeling and control of advanced motion systems, robotics for care and cure, automotive powertrains, and fusion plasmas.
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Sensor Fault Detection and Isolation in Big Data Environments:
Prof. Marios M. Polycarpou
President, IEEE Computational Intelligence Society
Director, KIOS Research Center for Intelligent Systems and Networks
Department of Electrical and Computer Engineering
University of Cyprus
Cyprusy
Prof. Marios M. Polycarpou
President, IEEE Computational Intelligence Society
Director, KIOS Research Center for Intelligent Systems and Networks
Department of Electrical and Computer Engineering
University of Cyprus
Cyprusy
Abstract:
The emergence of networked embedded systems and sensor/actuator networks has given rise to advanced monitoring and control applications, where a large amount of sensor data is collected and processed in real-time in order to achieve smooth and efficient operation of the underlying system. The current trend is towards larger and larger sensor data sets, leading to so called big data environments. However, in situations where faults arise in one or more of the sensing devices, this may lead to a serious degradation in performance or even to an overall system failure. The goal of this presentation is to motivate the need for fault diagnosis in complex distributed dynamical systems and to provide a methodology for detecting and isolating multiple sensor faults in a class of nonlinear dynamical systems. The detection of faults in sensor groups is conducted using robust analytical redundancy relations, formulated by structured residuals and adaptive thresholds. Various estimation algorithms will be presented and illustrated, and directions for future research will be discussed. Biography:
Marios M. Polycarpou is a Professor of Electrical and Computer Engineering and the Director of the KIOS Research Center for Intelligent Systems and Networks at the University of Cyprus. He received the B.A. degree in Computer Science and the B.Sc. degree in Electrical Engineering both from Rice University, Houston, TX, USA in 1987, and the M.S. and Ph.D. degrees in Electrical Engineering from the University of Southern California, Los Angeles, CA, in 1989 and 1992 respectively. Prior to joining the University of Cyprus as founding Department Chair in 2001, he was Professor of Electrical and Computer Engineering and Computer Science at the University of Cincinnati, Ohio, USA. His teaching and research interests are in intelligent systems and control, fault diagnosis, computational intelligence, adaptive and cooperative control, and large-scale systems. Dr. Polycarpou has published over 230 papers in these areas and is the holder of 3 patents.
Prof. Polycarpou is a Fellow of the IEEE and currently serves as the President of the IEEE Computational Intelligence Society. He has served as the Editor-in-Chief of the IEEE Transactions on Neural Networks and Learning Systems from 2004 until 2010. He participated in more than 60 research projects/grants, funded by several agencies and industry in Europe and the United States. In 2011, Dr. Polycarpou was awarded the prestigious European Research Council (ERC) Advanced Grant.
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Signal Processing via Sampled-Data Control - A Challenge to Go Beyond Shannon:
Prof. Yutaka Yamamoto
University of Kyoto, Japan
Prof. Yutaka Yamamoto
University of Kyoto, Japan
Abstract:
There has been remarkable progress in sampled-data control theory in the last two decades. The main achievement here is that there exists a digital (discrete-time) control law that takes the intersample behavior into account and makes the overall analog (continuous-time) performance optimal, in the sense of H-infinity norm. This naturally suggests its application to digital signal processing where the same hybrid nature of analog and digital is always prevalent. A crucial observation here is that the perfect band-limiting hypothesis, widely accepted in signal processing, is often inadequate for many practical situations. In practice, the original analog signals (sounds, images, etc.) are neither fully band-limited nor even close to be band-limited in the current processing standards. The present talk describes how sampled-data control theory can be applied to reconstruct the lost high-frequency components beyond the so-called Nyquist frequency, and how this new method can surpass the existing signal processing paradigm. We will also review some concrete examples for sound processing, recovery of high frequency components for MP3/AAC compressed audio signals, and super resolution for image (still/moving) processing. We will also review some crucial steps in leading this technology to the commercial success of 40 million sound processing chips.
Biography:
Yutaka Yamamoto received his B. S. and M. S. degrees in engineering from Kyoto University, Kyoto, Japan, in 1972 and 1974, respectively, and the M. S. and Ph. D. degrees in mathematics from the University of Florida, in 1976 and 1978, respectively. He is currently a professor at the Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics of Kyoto University. His research and teaching interests are in realization and robust control of distributed parameter systems, learning control systems, and sampled-data systems, its application to digital signal processing, with emphasis on sound and image processing.
Dr. Yamamoto received the Sawaragi memorial paper award in 1985, outstanding paper award of SICE in 1987 and in 1997, the best author award of SICE in 1990 and in 2000, the George S. Axelby Outstanding Paper Award in 1996, and the Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology Prizes for Science and Technology in 2007. He received the IEEE Control Systems Society Distinguished Member Award in 2009, and the Transition to Practice Award of the Control Systems Society in 2012, as well as the ISCIE Best Industrial Paper Award in 2009. He is a Fellow of the IEEE and SICE. He is currently President of the IEEE Control Systems Society. He has served as the Vice President for Technical Activities of the CSS for 2005-2006, and as Vice President for Publication Activities for 2007-2008. He was an associate editor of the IEEE Transactions on Automatic Control, Automatica, Systems and Control Letters, and is currently an associate editor of Mathematics of Control, Signals and Systems. He has served as a Senior Editor for the IEEE Transactions on Automatic Control for 2010-2011. He also served as an organizing committee member of the 35th CDC in 1996, MTNS '91 in Kobe, and as a member of program committees of several CDC's. He was the chair of the Steering Committee of MTNS, and served as General Chair of MTNS 2006. He is a past President of ISCIE of Japan.