Output-Dependent Switching Laws for Quadratic Stabilization of Switched Linear Stochastic Systems

Yufang Chang, Guisheng Zhai, Lianglin Xiong, Bo Fu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider global quadratic stabilization in probability for switched linear stochastic systems (SLSS). Assuming that no single subsystem is globally quadratically stable in probability (GQS-P), we propose both static and dynamic output-dependent switching laws such that the entire switched system is GQS-P. In the case of static output-dependent switching, the sufficient condition is expressed by a set of matrix inequalities, while the design of dynamic output-dependent switching is based on a convex combination of subsystems and a robust Luenberger observer for each subsystem. A numerical example is provided to show effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1796-1801
Number of pages6
ISBN (Electronic)9781728158549
DOIs
Publication statusPublished - 2020 Aug
Event32nd Chinese Control and Decision Conference, CCDC 2020 - Hefei, China
Duration: 2020 Aug 222020 Aug 24

Publication series

NameProceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020

Conference

Conference32nd Chinese Control and Decision Conference, CCDC 2020
CountryChina
CityHefei
Period20/8/2220/8/24

Keywords

  • convex combination
  • globally quadratically stable in probability (GQS-P)
  • linear matrix inequalities (LMIs)
  • output-dependent switching
  • Switched linear stochastic systems (SLSS)

ASJC Scopus subject areas

  • Decision Sciences (miscellaneous)
  • Automotive Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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