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


This paper 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
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Publication statusAccepted/In press - 2022


  • Asymptotic stability
  • asymptotic stability
  • finite-time stability.
  • Lyapunov methods
  • Markov processes
  • singularly perturbed systems
  • Stability criteria
  • Switches
  • Thermal stability
  • Transient analysis
  • transient performance

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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