Robust fault detection for Markovian jump systems with unreliable communication links

Abstract

This article addresses the problem of robust fault detection for Markovian jump linear systems with unreliable communication links. In the network communication channel, the effects of signal quantisation and measurement missing, which appears typically in a network environment, are taken into consideration simultaneously. A stochastic variable satisfying the Bernoulli random binary distribution is utilised to model the phenomenon of the measurements missing. The aim is to design a fault detection filter such that, for all unknown input and incomplete measurements, the error between the residual and weighted faults is made as small as possible. A sufficient condition for the existence of the desired fault detection filter is established in terms of a set of linear matrix inequalities. A simulation example is provided to illustrate the effectiveness and applicability of the proposed techniques.

Keywords:

• Markovian jumping system
• fault detection
• networked systems
• signal quantisation
• data missing

Acknowledgements

This work was supported by the Fundamental Research Funds for the Central Universities (Grant Nos. HIT.KLOF.2010019, HIT.NSRIF.201161 and HIT.NSRIF.2012031), the National Natural Science Foundation of China (61104101) and the China Postdoctoral Science Foundation (2011M500058) and by the Heilongjiang Postdoctoral Fund (LBH-Z11144).