Unbiased Minimum Variance Fault and State Estimation for Linear Discrete Time-Varying Two-Dimensional Systems

被引:109
|
作者
Wang, Youqing [1 ,2 ]
Zhao, Dong [2 ]
Li, Yueyang [3 ]
Ding, Steven X. [4 ]
机构
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
[2] Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
[3] Univ Jinan, Sch Elect Engn, Jinan 250022, Shandong, Peoples R China
[4] Univ Duisburg Essen, Inst Automat Control & Complex Syst AKS, D-47057 Duisburg, Germany
基金
中国国家自然科学基金;
关键词
Fault and state estimation; Kalman filter; minimum variance; time-varying system; two-dimensional system; DESIGN; OBSERVERS; INPUT;
D O I
10.1109/TAC.2017.2697210
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The fault and state estimation problem is addressed for a class of linear discrete time-varying two-dimensional systems subject to state and measurement noises. Two estimators are proposed to compute the estimation of the system state and/or fault recursively, both of which are unbiased with minimum variance. Through formulating the estimation problem as the solvability problem of the corresponding matrix equations of estimator gains and system constraint, the necessary and sufficient condition of the existence and the solution for the proposed estimators are given. An example is used to demonstrate the effectiveness of the proposed estimators.
引用
收藏
页码:5463 / 5469
页数:7
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