Switching Time Estimation of Piecewise Linear Systems. Application to Diagnosis

Analysing the behaviour of physical systems often leads to realise that a natural representation consists in building mixed continuous / discrete models. Multimodels or hybrid models are adapted representations for complex physical systems by introducing transitions (smooth or not) between local behaviours. This paper presents some technical points dealing with the determination of the time transition from one local model to another one. More generally, our purpose is to estimate, at each time, the state of the associated process.

[1]  Alexander Medvedev.  State estimation and fault detection by a bank of continuous finite-memory filters , 1998 .

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

[3]  L. Ljung,et al.  Identification of hybrid systems via mixed-integer programming , 2001 .

[4]  I. Hiskens.  Identifiability of hybrid system models , 2000, Proceedings of the 2000. IEEE International Conference on Control Applications. Conference Proceedings (Cat. No.00CH37162).

[5]  James D. Hamilton.  A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle , 1989 .

[6]  Tor Arne Johansen,et al.  Identification of non-linear system structure and parameters using regime decomposition , 1995, Autom..

[7]  A..  Diagnosing Hybrid Systems : a Bayesian Model Selection Approach , 2005 .

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

[9]  Silvio Simani,et al.  Identification and fault diagnosis of nonlinear dynamic processes using hybrid models , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).

[10]  Vincent Verdult,et al.  Identification of a weighted combination of multivariable local linear state-space systems from input and output data , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[11]  Feng Zhao,et al.  FAULT ISOLATION IN HYBRID SYSTEMS COMBINING MODEL BASED DIAGNOSIS AND SIGNAL PROCESSING , 2000 .

[12]  David F. Hendry,et al.  Computer Automation of General-to-Specific Model Selection Procedures , 2001 .

[13]  Angelo Alessandri,et al.  Design of Luenberger Observers for a Class of Hybrid Linear Systems , 2001, HSCC.