Fault estimation for a class of linear parameter varying systems with Markovian jumps

被引：9
作者：
Huang, Sheng-Juan [1 ,2 ]
Yang, Guang-Hong [1 ,3 ]
机构：
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110004, Peoples R China
[2] Univ Sci & Technol Liaoning, Sch Sci, Anshan 114051, Peoples R China
[3] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110004, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2016年 / 353卷 / 17期
关键词：
SUGENO FUZZY-SYSTEMS; H-INFINITY CONTROL; TOLERANT CONTROLLER-DESIGN; OUTPUT-FEEDBACK CONTROL; TIME-DELAY; STOCHASTIC-SYSTEMS; OBSERVER DESIGN; VEHICLE; IDENTIFICATION; FILTER;
D O I：
10.1016/j.jfranklin.2016.09.003
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 studies the problem of fault estimation for a class of linear parameter varying (LPV) Markovian jump systems (MJSs) with actuator and sensor faults. A new fault estimation scheme is presented for the LPV MJS, where a novel min-max regulator (MMR) based on the Cholesky decomposition technique is designed to adjust the parameters in the fault estimator so that the states, actuator and sensor faults are able to be estimated simultaneously with good accuracy. Then, the designed observer gains guarantee the stochastic stability of the overall error system with a prescribed Ho. performance. Finally, a numerical example is given to illustrate the effectiveness and advantages of the proposed methods. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：4680 / 4700
页数：21
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