Finite-Time Stabilization of Markov Switching Singularly Perturbed Models

Wenhai Qi, Can Zhang, Guangdeng Zong, Choon Ki Ahn, Huaicheng Yan

Research output: Contribution to journalArticlepeer-review

Abstract

This brief is concerned with the issue of finite-time stabilization of discrete-time stochastic singularly perturbed models, in which the stochastic process is regulated by a Markov chain with partially unknown transition probabilities (TPs). The slow-state and fast-state variable are considered in the modeling, and the corresponding Markov switching model with a singularly perturbed parameter is obtained in a unified framework. Ill-conditioned problems caused by a small singular perturbation parameter are prevented by developing a finite-time stability criterion for the resultant system. Furthermore, feasible conditions are derived for the desired finite-time state feedback controller by using matrix inequalities that are independent of the singularly perturbed parameter. Finally, a gear-driven DC motor model is applied to illustrate the effectiveness of the described control strategy.

Original languageEnglish
Pages (from-to)3535-3539
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Volume69
Issue number8
DOIs
Publication statusPublished - 2022 Aug 1

Keywords

  • Singularly perturbed systems
  • asymptotic stability
  • finite-time stability
  • transient performance

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Finite-Time Stabilization of Markov Switching Singularly Perturbed Models'. Together they form a unique fingerprint.

Cite this