Switching systems: active mode recognition, identification of the switching law

The problem of the estimation of the discrete state of a switching system is studied. The knowledge of the switching law is essential for this kind of system as it simplifies their manipulation for control purposes. This paper investigates the use of a model-based diagnosis method for the determination of the active mode at each time point based on the system input/output data. The issue of the parametric identification of the switching law is also addressed.

[1]  Alberto L. Sangiovanni-Vincentelli,et al.  Design of Observers for Hybrid Systems , 2002, HSCC.

[2]  Bart De Schutter,et al.  Equivalence of hybrid dynamical models , 2001, Autom..

[3]  George J. Pappas,et al.  Observability of Switched Linear Systems in Continuous Time , 2005, HSCC.

[4]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[5]  W. P. M. H. Heemels,et al.  Comparison of Four Procedures for the Identification of Hybrid Systems , 2005, HSCC.

[6]  Magnus Egerstedt,et al.  ASYMPTOTIC OBSERVERS FOR DISCRETE-TIME SWITCHED LINEAR SYSTEMS , 2005 .

[7]  M. Egerstedt,et al.  Pathwise observability and controllability are decidable , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[8]  Alberto Bemporad,et al.  Identification of piecewise affine systems via mixed-integer programming , 2004, Autom..

[9]  Alberto Bemporad,et al.  Observability and controllability of piecewise affine and hybrid systems , 2000, IEEE Trans. Autom. Control..

[10]  Ron J. Patton,et al.  Robustness in Model-Based Fault Diagnosis: The 1995 Situation , 1995 .

[11]  J. Gerfler.  FAULT DETECTION AND ISOLATION USING PARITY RELATIONS , 2003 .

[12]  Didier Maquin,et al.  Diagnostic des systèmes à commutation , approche par la méthode de l ’ espace de parité Elom Ayih Domlan , 2004 .

[13]  Vincent Cocquempot,et al.  Switching Time Estimation and Fault Detection for Hybrid Systems Using Structured Parity Residuals , 2003 .

[14]  Jean Charles Gilbert,et al.  Numerical Optimization: Theoretical and Practical Aspects , 2003 .

[15]  J. Frédéric Bonnans,et al.  Numerical Optimization: Theoretical and Practical Aspects (Universitext) , 2006 .

[16]  Didier Maquin,et al.  Parameter estimation of switching piecewise linear system , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[17]  Manfred Morari,et al.  A clustering technique for the identification of piecewise affine systems , 2001, Autom..

[18]  R. Vidal,et al.  Observability and identifiability of jump linear systems , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[19]  K. Ito,et al.  On State Estimation in Switching Environments , 1970 .

[20]  Alberto Bemporad,et al.  Control of systems integrating logic, dynamics, and constraints , 1999, Autom..

[21]  K. Fu,et al.  On state estimation in switching environments , 1968 .

[22]  Kristin P. Bennett,et al.  Multicategory Classification by Support Vector Machines , 1999, Comput. Optim. Appl..

[23]  Inseok Hwang,et al.  Observability criteria and estimator design for stochastic linear hybrid systems , 2003, 2003 European Control Conference (ECC).

[24]  V. Borkar,et al.  A unified framework for hybrid control: model and optimal control theory , 1998, IEEE Trans. Autom. Control..

[25]  Anders Rantzer,et al.  Computation of piecewise quadratic Lyapunov functions for hybrid systems , 1997, 1997 European Control Conference (ECC).

[26]  O. Mangasarian,et al.  Multicategory discrimination via linear programming , 1994 .

[27]  Elom Ayih Domlan.  Diagnostic des systèmes à changement de régime de fonctionnement , 2006 .