Fault Detection Filtering for Nonlinear Switched Stochastic Systems

Fault Detection Filtering for Nonlinear Switched Stochastic Systems
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非线性切换随机系统的故障检测滤波

DOI:
10.1109/tac.2015.2465091
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发表时间:
2016-05
影响因子:
6.8
通讯作者:
Song Yong-Duan
Song Yong-Duan
中科院分区:
计算机科学2区
文献类型:
--
作者:
Su Xiaojie;Shi Peng;Wu Ligang;Song Yong-Duan

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本文在T-S模糊框架下解决了非线性开关随机系统的故障检测滤波问题。研究了具有布朗运动的非线性开关系统的鲁棒故障检测技术。基于观测器的故障检测模糊滤波器作为残差发生器,将所提出的故障检测问题表述为一个模糊滤波问题。利用平均停留时间技术和分段李雅普诺夫函数技术,设计了模糊参数相关的故障检测滤波器,保证误差系统均方指数稳定,并具有加权H∞误差性能。然后,利用线性化处理技术建立了故障检测模糊滤波器的可解性条件。最后,通过仿真验证了所提故障检测技术的有效性。
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.
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