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|Title:||Fault detection filtering for nonlinear switched stochastic systems|
|Citation:||IEEE Transactions on Automatic Control, 2016; 61(5):1310-1315|
|Publisher:||Institute of Electrical and Electronics Engineers|
|Xiaojie Su, Peng Shi, Ligang Wu, and Yong-Duan Song|
|Abstract:||In this note, the fault detection filtering problem is solved for nonlinear switched stochastic system in the T-S fuzzy framework. Our attention is concentrated on the construction of a robust fault detection technique to the nonlinear switched system with Brownian motion. Based on observer-based fault detection fuzzy filter as a residual generator, the proposed fault detection is formulated as a fuzzy filtering problem. By the utilization of the average dwell time technique and the piecewise Lyapunov function technique, the fuzzy-parameter-dependent fault detection filters are designed that guarantee the resulted error system to be mean-square exponential stable with a weighted H∞ error performance. Then, the corresponding solvability condition for the fault detection fuzzy filter is also established by the linearization procedure technique. Finally, simulation has been presented to show the effectiveness of the proposed fault detection technique.|
|Keywords:||Fault detection; fuzzy filtering; stochastic systems; switched systems|
|Rights:||© 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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