Optimal residual design for fault diagnosis using multi-objective optimization and genetic algorithms

This paper develops a new approach to the design of optimal residuals in order to diagnose incipient faults based on multi-objective optimization and genetic algorithms. In this approach the residual is generated via an observer. To reduce false and missed alarm rates in fault diagnosis, a number of performance indices are introduced into the observer design. Some performance indices are expressed in the frequency domain to take account of the frequency distributions of faults, noise and modelling uncertainties. All objectives then are reformulated into a set of inequality constraints on performance indices. A genetic algorithm is thus used to search for an optimal solution to satisfy these inequality constraints on performance indices. The approach developed is applied to a flight control system example, and simulation results show that incipient sensor faults can be detected reliably in the presence of modelling uncertainty.

[1]  R. J. Patton,et al.  Parameter-Insensitive Technique for Aircraft Sensor Fault Analysis , 1987 .

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

[3]  R. Patton,et al.  Analysis of the technique of robust eigenstructure assignment with application to aircraft control , 1988 .

[4]  J. Gertler,et al.  Optimal residual decoupling for robust fault diagnosis , 1995 .

[5]  Janos Gertler,et al.  Robust FDI systems and H/sub /spl infin//-optimization-disturbances and tall fault case , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[6]  R. Patton,et al.  A Review of Parity Space Approaches to Fault Diagnosis , 1991 .

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

[8]  Guo-Ping Liu,et al.  Robust control design via eigenstructure assignment, genetic algorithms and gradient-based optimisation , 1994 .

[9]  P. Frank,et al.  Fault detection via optimally robust detection filters , 1989, Proceedings of the 28th IEEE Conference on Decision and Control,.

[10]  R. Patton,et al.  Design of a low-sensitivity, minimum norm and structurally constrained control law using eigenstructure assignment , 1991 .

[11]  Jie Chen,et al.  Robust residual generation for model-based fault diagnosis of dynamic systems. , 1995 .

[12]  Rami Mangoubi,et al.  Robust estimation in fault detection , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[13]  V. Zakian,et al.  Design of dynamical and control systems by the method of inequalities , 1973 .