Frontiers of Electrical and Electronic Engineering >

2009 , Vol. 4 >Issue 1: 60 - 65

DOI: https://doi.org/10.1007/s11460-009-0011-4

RESEARCH ARTICLE

Fault detection for a class of Markov jump systems with unknown disturbances

  • Shuping HE ,
  • Fei LIU
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  • Institute of Automation, Jiangnan University, Wuxi 214122, China

Published date: 05 Mar 2009

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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Abstract

An optimized fault detection observer is designed for a class of Markov jump systems with unknown disturbances. By reconstructing the system, the residual error dynamic characteristics of unknown input and fault signals, including unknown disturbances and modeling error are obtained. The energy norm indexes of disturbance and fault signals of the residual error are selected separately to reflect the restraint of disturbance and the sensitivity of faults, and the design of the fault detection observer is described as an optimization problem. By using the constructed Lyapunov function and linear matrix inequalities, a sufficient condition that the solution to the fault detection observer exists is given and proved, and an optimized design approach is presented. The designed observer makes the systems have stochastic stability and better capability of restraining disturbances, and the given norm index is satisfied. Simulation results demonstrate that the proposed observer can detect the faults sensitively, and the influence of unknown disturbance on residual error can be restrained to a given range.

Key words： Markov jump systems; fault detection; optimized observer; stochastic stability; linear matrix inequalities

Cite this article

Shuping HE , Fei LIU . Fault detection for a class of Markov jump systems with unknown disturbances[J]. Frontiers of Electrical and Electronic Engineering, 2009 , 4(1) : 60 -65 . DOI: 10.1007/s11460-009-0011-4

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 60574001), the Program for New Century Excellent Talents in University (No. 050485).

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