Robust fault diagnosis and fault‐tolerant control for non‐Gaussian uncertain stochastic distribution control systems
Robust fault diagnosis and fault‐tolerant control for non‐Gaussian uncertain stochastic distribution control systems
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DOI：
10.1002/rnc.3632
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发表时间：
2017-07
影响因子：
3.9
通讯作者：
Yuancheng Sun;L. Yao
中科院分区：
文献类型：
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作者：
Yuancheng Sun;L. Yao
随机分布控制系统故障诊断的目的是利用测量输入和系统输出的概率密度函数来获得故障估计信息。针对具有概率密度函数逼近误差的非高斯不确定随机分布控制系统，提出了一种故障诊断和滑模容错控制算法。将模型不确定性引起的未知输入视为外生干扰，利用未知输入观测器的思想构造增广观测误差动态系统。对观测误差动态系统进行了稳定性分析，保证了H∞性能。基于故障估计信息和期望输出概率密度函数，设计滑模容错控制器，使故障后输出概率密度函数仍跟踪期望分布。该方法避免了输入不确定性给故障诊断观测器设计带来的困难，实现了故障诊断与容错控制的集成。两个不同的说明的例子来证明所提出的算法的有效性。版权所有© 2016约翰威利父子有限公司.
The purpose of fault diagnosis of stochastic distribution control systems is to use the measured input and the system output probability density function to obtain the fault estimation information. A fault diagnosis and sliding mode fault‐tolerant control algorithms are proposed for non‐Gaussian uncertain stochastic distribution control systems with probability density function approximation error. The unknown input caused by model uncertainty can be considered as an exogenous disturbance, and the augmented observation error dynamic system is constructed using the thought of unknown input observer. Stability analysis is performed for the observation error dynamic system, and the H∞ performance is guaranteed. Based on the information of fault estimation and the desired output probability density function, the sliding mode fault‐tolerant controller is designed to make the post‐fault output probability density function still track the desired distribution. This method avoids the difficulties of design of fault diagnosis observer caused by the uncertain input, and fault diagnosis and fault‐tolerant control are integrated. Two different illustrated examples are given to demonstrate the effectiveness of the proposed algorithm. Copyright © 2016 John Wiley & Sons, Ltd.