Advances in the Theory of Control, Signals and Systems with Physical Modeling
In the 60's, control, signals and systems had a common linear algebraic background and, according to their evolution, their respective backgrounds have now dramatically differed. Recovering such a common background, especially in the nonlinear context, is
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Jean Lévine and Philippe Müllhaupt (Eds.)
Advances in the Theory of Control, Signals and Systems with Physical Modeling
ABC
Series Advisory Board P. Fleming, P. Kokotovic, A.B. Kurzhanski, H. Kwakernaak, A. Rantzer, J.N. Tsitsiklis
Editors Jean Lévine CAS, Unité Mathématiques et Systèmes MINES-ParisTech 35, rue Saint-Honoré 77300 Fontainebleau France E-mail: [email protected] Philippe Müllhaupt Laboratoire d’Automatique Faculté des Sciences de l’Ingénieur Station 9 CH-1015 Lausanne Switzerland E-mail: [email protected]
ISBN 978-3-642-16134-6
e-ISBN 978-3-642-16135-3
DOI 10.1007/978-3-642-16135-3 Lecture Notes in Control and Information Sciences
ISSN 0170-8643
Library of Congress Control Number: 2010936509 c
2010 Springer-Verlag Berlin Heidelberg
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Advances in the Theory of Control, Signals, and Systems, with Physical Modeling Jean L´evine1 and Philippe M¨ullhaupt2
1 Introduction This book gathers articles that have been invited for presentation in the framework of a Bernoulli Programme, held at the Bernoulli Center in Lausanne (Switzerland) from January to June 2009. This Programme mainly consisted of three workshops aiming at reviewing the advances in the theory of control, signals, and systems, with a particular emphasis on their relationship to physical modeling. More precisely, the aim of this series of three workshops was to • bring together knowledge and know-how from the communities of control, signals and systems, • focus on the theoretical advances in these areas and examine the possibilities of new convergences between them, • contribute to the enhancement of the dialogue between theoretical laboratories and more practically oriented units and industries. In the 60’s, control, signals and systems had a common linear algebraic background and, according to their evolution, their respective backgrounds have now dramatically differed. Recovering such a common background, especially in the nonlinear context, is currently a fully open question. In most contributions, emphasis has been put on physical modeling,
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