Fault estimation for time-varying Markovian jump systems with randomly occurring nonlinearities and time delays

被引:25
|
作者
Ren, Weijian [1 ]
Wang, Chunlei [1 ]
Lu, Yang [2 ]
机构
[1] Northeast Petr Univ, Coll Elect & Informat Engn, Daqing 163318, Peoples R China
[2] Heilongjiang Bayi Agr Univ, Coll Informat Technol, Daqing 163318, Peoples R China
基金
中国国家自然科学基金;
关键词
NEURAL-NETWORKS; STATE ESTIMATION; LINEAR-SYSTEMS; STABILIZATION; STABILITY; DIAGNOSIS;
D O I
10.1016/j.jfranklin.2016.11.018
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is concerned with the fault estimation problem for a class of time-varying Markovian jump systems including randomly occurring nonlinearities (RONs) and multiple time-varying stochastic communication delays. Both the parameters and the nonlinear function are considered in the time varying system, where the Markov chain is adopted to reflect the mode transformation phenomenon at different times. The multiple time-varying stochastic communication delays are introduced via stochastic variable sequences following Bernoulli distribution. Such a set of Bernoulli sequences comprising independent variables is utilized to represent the generation of nonlinear interferences in the form of random. The main objective proposed in this paper is to finish a time-varying fault estimator in order to meet the prescribed average filtering performance constraint. Through adopting the Lyapunov Krasovakii functional as well as the stochastic theory, several corresponding requirements to guarantee such designed estimator are given by LMI approach. A simulation is provided for verifying the feasibility of the addressed methods. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1388 / 1402
页数:15
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