Abstract
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 language | English |
---|---|
Journal | IEEE Transactions on Circuits and Systems II: Express Briefs |
DOIs | |
Publication status | Accepted/In press - 2022 |
Keywords
- 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