Gain-Scheduled Robust Fault Detection on Time-Delay Stochastic Nonlinear Systems

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Yin, Yanyan, Shi, Peng and Liu, Fei (2011) Gain-Scheduled Robust Fault Detection on Time-Delay Stochastic Nonlinear Systems. IEEE Transactions on Industrial Electronics, 58 (10). pp. 4908-4916. ISSN 0278-0046


This paper studies the problem of continuous gain-scheduled robust fault detection (RFD) on a class of timedelay stochastic nonlinear systems with partially known jump rates. By means of gradient linearization procedure, stochastic linear models and filter-based residual signal generators are constructed in the vicinity of selected operating states. Furthermore, in order to guarantee the sensitivity to faults and robustness against unknown inputs, an RFD filter (RFDF) is designed for such linear models by first designing H∞ filters that minimize the influences of the disturbances and modeling uncertainties and then a new performance index that increases the sensitivity to faults. Subsequently, a sufficient condition on the existence of RFDF is established in terms of linear matrix inequality techniques. Finally, a continuous gain-scheduled approach is employed to design continuous RFDFs on the entire nonlinear jump system. A simulation example is given to illustrate that the proposed RFDF can detect the faults correctly and shortly after the occurrences.

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Item type Article
DOI 10.1109/TIE.2010.2103537
Official URL
Subjects Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > SEO Classification > 970118 Expanding Knowledge in Law and Legal Studies
Keywords ResPubID24778, continuous gain scheduling, filter, Markov jump system, MJS, nonlinearities, robust fault detection, RFD, nonlinear filter
Citations in Scopus 88 - View on Scopus
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