Fault detection and isolation for hybrid systems using structured parity residuals

Many physical systems are hybrid which means that both continuous and discrete states influence their dynamic behavior. The time evolution of the continuous states is constrained by vector fields that change due to internal or external discrete events. This paper is concerned with FDI (fault detection and isolation) for this kind of system. Two types of faults may be considered for hybrid dynamical systems depending on the component of the model that is affected by faults that may affect the current mode behavior or may affect the trajectory of the discrete evolution. The general principle of model-based FDI algorithms is to check the consistency of the known signals (inputs and outputs) w.r.t. a model. Parity residuals are special signals that reflect that consistency. As a direct consequence, these residuals may be used to detect faults in a given mode. Moreover, under the hypothesis that all modes are discernable, on-line mode identification is also possible which leads to diagnose the faults affecting the discrete sequence. In this paper, necessary and sufficient conditions are derived to guarantee the discernability between two modes and the complete FDI methodology, using parity residuals, is described.

[1]  J.J. Gertler,et al.  Survey of model-based failure detection and isolation in complex plants , 1988, IEEE Control Systems Magazine.

[2]  Abd-El-Kader Sahraoui Vers une approche globale de surveillance des systèmes à événements discrets , 1992 .

[3]  A. Haddad,et al.  On the Controllability and Observability of Hybrid Systems , 1988, 1988 American Control Conference.

[4]  A. Isidori,et al.  On the problem of residual generation for fault detection in nonlinear systems and some related facts , 1999, 1999 European Control Conference (ECC).

[5]  Bart De Schutter,et al.  Optimal Control of a Class of Linear Hybrid Systems with Saturation , 1999, SIAM J. Control. Optim..

[6]  P. Frank On-line fault detection in uncertain nonlinear systems using diagnostic observers: a survey , 1994 .

[7]  H. Witsenhausen A class of hybrid-state continuous-time dynamic systems , 1966 .

[8]  G. Bornard,et al.  Observability for any u(t) of a class of nonlinear systems , 1980, 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[9]  Michèle Basseville,et al.  Fault Detection and Isolation in Nonlinear Dynamic Systems: A Combined Input-Output and Local Approach , 1998, Autom..

[10]  Antonio Ramírez-Treviño,et al.  Diagnosability of discrete event systems: a Petri net based approach , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[11]  J. Gauthier,et al.  Observability and observers for non-linear systems , 1986, 1986 25th IEEE Conference on Decision and Control.

[12]  Janos J. Gertler,et al.  Analytical Redundancy Methods in Fault Detection and Isolation , 1991 .

[13]  Gabor Karsai,et al.  Building observers to address fault isolation and control problems in hybrid dynamic systems , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[14]  Paul M. Frank,et al.  Comparison of Observer-Based Fault Detection Approaches , 1994 .

[15]  A. Krener,et al.  Nonlinear controllability and observability , 1977 .

[16]  Ron J. Patton,et al.  Robust Model-Based Fault Diagnosis: The State of the ART , 1994 .

[17]  Paul M. Frank,et al.  Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results , 1990, Autom..

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

[19]  S. Shankar Sastry,et al.  Observability of Linear Hybrid Systems , 2003, HSCC.

[20]  Cyrille Christophe Surveillance des systèmes non linéaires : application aux machines électriques , 2001 .

[21]  René David,et al.  Petri nets and grafcet - tools for modelling discrete event systems , 1992 .

[22]  Stefan Pettersson,et al.  Analysis and Design of Hybrid Systems , 1999 .

[23]  Sette Diop,et al.  Elimination in control theory , 1991, Math. Control. Signals Syst..

[24]  Paul M. Frank,et al.  Fault Diagnosis in Dynamic Systems , 1993, Robotics, Mechatronics and Manufacturing Systems.

[25]  Marcel Staroswiecki,et al.  Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems , 2001, Autom..

[26]  Rolf Isermann,et al.  Process fault detection based on modeling and estimation methods - A survey , 1984, Autom..

[27]  Janos Gertler,et al.  Fault detection and diagnosis in engineering systems , 1998 .

[28]  Walter Murray Wonham,et al.  On observability of discrete-event systems , 1988, Inf. Sci..

[29]  Michael S. Branicky,et al.  General Hybrid Dynamical Systems: Modeling, Analysis, and Control , 1996, Hybrid Systems.

[30]  Marcel Staroswiecki,et al.  A Parity Space Approach for Monitoring Inequality Constraints Part 2: Dynamic Case , 1999 .

[31]  A. Willsky,et al.  Analytical redundancy and the design of robust failure detection systems , 1984 .

[32]  Thomas A. Henzinger,et al.  The theory of hybrid automata , 1996, Proceedings 11th Annual IEEE Symposium on Logic in Computer Science.