Volume 28, Issue 6 pp. 2191-2208
RESEARCH ARTICLE

Inner approximations of domains of attraction for a class of switched systems by computing Lyapunov-like functions

Xiuliang Zheng

Xiuliang Zheng

State Key Laboratory of Software Development Environment, Key Laboratory of Mathematics Informatics and Behavioral Semantics, School of Mathematics and Systems Science, Beihang University, Beijing, China

College of Science, Hebei North University, Zhangjiakou, China

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Zhikun She

Corresponding Author

Zhikun She

State Key Laboratory of Software Development Environment, Key Laboratory of Mathematics Informatics and Behavioral Semantics, School of Mathematics and Systems Science, Beihang University, Beijing, China

Correspondence

Zhikun She, State Key Laboratory of Software Development Environment, Key Laboratory of Mathematics Informatics and Behavioral Semantics, School of Mathematics and Systems Science, Beihang University, Beijing 100191, China.

Email: [email protected]

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Quanyi Liang

Quanyi Liang

State Key Laboratory of Software Development Environment, Key Laboratory of Mathematics Informatics and Behavioral Semantics, School of Mathematics and Systems Science, Beihang University, Beijing, China

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Meilun Li

Meilun Li

State Key Laboratory of Software Development Environment, Key Laboratory of Mathematics Informatics and Behavioral Semantics, School of Mathematics and Systems Science, Beihang University, Beijing, China

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First published: 13 December 2017
Citations: 20

Summary

Domain of attraction plays an important role in control systems analysis, which is usually estimated by sublevel sets of Lyapunov functions. In this paper, based on the concept of common Lyapunov-like functions, we propose an iteration method for estimating domains of attraction for a class of switched systems, where the state space is divided into several regions, each region is described by polynomial inequalities, and any region has no intersection among with each other. Starting with an initial inner estimate of domain of attraction, we first present a theoretical framework for obtaining a larger inner estimate by iteratively computing common Lyapunov-like functions. Then, for obtaining a required initial inner estimate of domain of attraction, we propose a higher-order truncation and linear semidefinite programming–based method for computing a common Lyapunov function. Successively, the theoretical framework is under-approximatively realized by using S-procedure and sum-of-squares programming, associated with a coordinatewise iteration idea. Finally, we implement our method and test it on some examples with comparisons. These computation and comparison results show the advantages of our method.

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