Loo-gain filtering of semi-Markov jump systems subjected to persistent bounded disturbances?

被引：2

作者：

Ding, Yucai ^{[1
]}

Mei, Xu ^{[1
]}

Cheng, Jun ^{[2
]}

Shi, Kaibo ^{[3
]}

机构：

[1] Southwest Univ Sci & Technol, Sch Sci, Mianyang 621010, Peoples R China

[2] Guangxi Normal Univ, Coll Math & Stat, Guilin 541006, Peoples R China

[3] Chengdu Univ, Sch Informat Sci & Engn, Chengdu 610106, Peoples R China

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2022年 / 115卷

关键词：

Semi-Markov jump systems; Input-to-state stability; Loo-gain filtering; Persistent bounded disturbances; SLIDING MODE CONTROL; TO-STATE STABILITY; LINEAR-SYSTEMS; ROBUST STABILIZATION; NONLINEAR-SYSTEMS; DESIGN; DELAY;

D O I：

10.1016/j.cnsns.2022.106778

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this work, the problem of Loo-gain filtering of semi-Markov jump systems (S-MJSs) subjected to persistent bounded disturbances is investigated. We first provide a sufficient condition for input-to-state stability (ISS) of the systems under consideration. The analytical result of ISS is then recast as a linear matrix inequality (LMI) feasibility problem by using the S-procedure. Based on the ISS analysis, a novel Loo-gain filter design scheme is developed. The resulting filter ensures the trajectories of the estimation error at steady state to be bounded in the mean sense and makes the peak of the estimation error as small as possible under the effect of the external disturbances. Simulation results demonstrate the effectiveness of our proposed design scheme.(c) 2022 Elsevier B.V. All rights reserved.

引用

页数：15

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