SMC for Discrete Semi-Markov Switching Slow Sampling Singularly Perturbed Models With Applications

Wenhai Qi; Ning Zhang; Guangdeng Zong; Choon Ki Ahn

doi:10.1109/TCSI.2024.3355445

SMC for Discrete Semi-Markov Switching Slow Sampling Singularly Perturbed Models With Applications

Wenhai Qi, Ning Zhang, Guangdeng Zong, Choon Ki Ahn

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

The sliding mode control (SMC) is addressed for discrete-time semi-Markov switching slow sampling singularly perturbed models. Under only the part known semi-Markov kernel, the ϵ-dependent sliding function is designed for the underlying system. Based on the upper bound of the sojourn time of each system mode, sufficient conditions are obtained for mean-square stability. Then, a strategy to estimate the upper bound of the singularly perturbed parameter is given under an incomplete semi-Markov kernel. Moreover, an appropriate SMC scheme is synthesized to drive the system states onto the pre-specified sliding region. An inverted pendulum model is adopted to verify the practicability of the proposed strategy.

Original language	English
Pages (from-to)	1910-1919
Number of pages	10
Journal	IEEE Transactions on Circuits and Systems I: Regular Papers
Volume	71
Issue number	4
DOIs	https://doi.org/10.1109/TCSI.2024.3355445
Publication status	Published - 2024 Apr 1

Bibliographical note

Publisher Copyright:
© 2004-2012 IEEE.

Keywords

Sliding mode control
mean-square stability
singularly perturbed parameter

ASJC Scopus subject areas

Hardware and Architecture
Electrical and Electronic Engineering

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10.1109/TCSI.2024.3355445

Cite this

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abstract = "The sliding mode control (SMC) is addressed for discrete-time semi-Markov switching slow sampling singularly perturbed models. Under only the part known semi-Markov kernel, the ϵ-dependent sliding function is designed for the underlying system. Based on the upper bound of the sojourn time of each system mode, sufficient conditions are obtained for mean-square stability. Then, a strategy to estimate the upper bound of the singularly perturbed parameter is given under an incomplete semi-Markov kernel. Moreover, an appropriate SMC scheme is synthesized to drive the system states onto the pre-specified sliding region. An inverted pendulum model is adopted to verify the practicability of the proposed strategy.",

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SMC for Discrete Semi-Markov Switching Slow Sampling Singularly Perturbed Models With Applications

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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