Stochastic Observability and Convergent Analog State Estimation of Randomly Switched Linear Systems With Unobservable Subsystems

被引:10
作者
Wang, Le Yi [1 ]
Yin, George [2 ]
Lin, Feng [1 ]
Polis, Michael P. [3 ]
Chen, Wen [4 ]
机构
[1] Wayne State Univ, Dept Elect & Comp Engn, Detroit, MI 48202 USA
[2] Univ Connecticut, Dept Math, Storrs, CT 06269 USA
[3] Oakland Univ, Sch Engn & Comp Sci, Rochester, MI 48309 USA
[4] Wayne State Univ, Div Engn Technol, Detroit, MI 48202 USA
关键词
Observers; Observability; Switches; Convergence; Stochastic processes; Linear systems; Heuristic algorithms; hybrid systems; large deviation principles (LDP); observer design; randomly switched linear systems (RSLSs); stochastic observability; COMMUNICATION ERASURE CHANNELS; HYBRID DYNAMICAL-SYSTEMS; NETWORKED SYSTEMS; PERFORMANCE; IMPACT; CONTROLLABILITY; ALGORITHMS;
D O I
10.1109/TAC.2022.3148602
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 article investigates observability and observer design for randomly switched linear systems (RSLSs) whose subsystems are all unobservable. Conditions for determining the analog state uniquely during operation, defined as stochastic observability, are studied. This article establishes probabilistic descriptions of stochastic observability for fast switching RSLSs. Design methods for subsystem observers and their organization for estimating the entire state are introduced. Convergence properties are established, including strong convergence and exponential convergence rate. Estimation error probabilities under finite data are derived by using the large deviation principles. Some critical structural conditions are characterized that permit organization of subsystem observers for achieving a convergent observer for the entire state. Examples and simulation case studies are presented to illustrate the main results of this article.
引用
收藏
页码:898 / 911
页数:14
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