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

7 Citations (Scopus)


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
Issue number8
Publication statusPublished - 2022 Aug 1

Bibliographical note

Funding Information:
This work was supported in part by the Natural Science Foundation of Shandong under Grant ZR2019YQ29 and Grant ZR2021MF083; in part by the National Natural Science Foundation of China under Grant 62073188 and Grant 61773235; and in part by the National Research Foundation of Korea (NRF) Grant funded by the Korea Government (Ministry of Science and ICT) under Grant NRF-2020R1A2C1005449.

Publisher Copyright:
© 2004-2012 IEEE.


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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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