Finite-Time H∞Asynchronous Control for Nonlinear Markov Jump Distributed Parameter Systems via Quantized Fuzzy Output-Feedback Approach

Xiaona Song; Mi Wang; Choon Ki Ahn; Shuai Song

doi:10.1109/TCYB.2019.2936827

Finite-Time H_∞Asynchronous Control for Nonlinear Markov Jump Distributed Parameter Systems via Quantized Fuzzy Output-Feedback Approach

Xiaona Song, Mi Wang, Choon Ki Ahn, Shuai Song

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

60 Citations (Scopus)

Abstract

This article focuses on the asynchronous output-feedback control design for a class of nonlinear Markov jump distributed parameter systems based on a hidden Markov model. Initially, the considered systems are represented by a Takagi-Sugeno fuzzy model via a sector nonlinearity approach. Furthermore, asynchronous quantizers are introduced to save the limited communication resource in engineering applications. Then, based on the Lyapunov direct method and some inequality techniques, a series of novel stability criteria, which guarantee the finite-time boundedness and H∞disturbance attenuation performance of the target plants, is established in the form of spatial differential linear matrix inequalities. Finally, a simulation study is provided to verify the viability of the developed approach.

Original language	English
Article number	8826312
Pages (from-to)	4098-4109
Number of pages	12
Journal	IEEE Transactions on Cybernetics
Volume	50
Issue number	9
DOIs	https://doi.org/10.1109/TCYB.2019.2936827
Publication status	Published - 2020 Sept

Bibliographical note

Funding Information:
Manuscript received May 7, 2019; revised July 8, 2019; accepted August 12, 2019. Date of publication September 6, 2019; date of current version August 18, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61976081 and Grant U1604146, in part by the Foundation for the University Technological Innovative Talents of Henan Province under Grant 18HASTIT019, and in part by the National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning under Grant NRF-2017R1A1A1A05001325. This article was recommended by Associate Editor L. Zhang. (Corresponding author: Choon Ki Ahn.) X. Song and M. Wang are with the School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China (e-mail: xiaona_97@163.com; wangmi_17@163.com).

Publisher Copyright:
© 2013 IEEE.

Keywords

Asynchronous output-feedback control
Markov jump
Takagi-Sugeno fuzzy model
distributed parameter systems (DPSs)
hidden Markov model (HMM)

ASJC Scopus subject areas

Software
Control and Systems Engineering
Information Systems
Human-Computer Interaction
Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/TCYB.2019.2936827

Cite this

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title = "Finite-Time H∞Asynchronous Control for Nonlinear Markov Jump Distributed Parameter Systems via Quantized Fuzzy Output-Feedback Approach",

abstract = "This article focuses on the asynchronous output-feedback control design for a class of nonlinear Markov jump distributed parameter systems based on a hidden Markov model. Initially, the considered systems are represented by a Takagi-Sugeno fuzzy model via a sector nonlinearity approach. Furthermore, asynchronous quantizers are introduced to save the limited communication resource in engineering applications. Then, based on the Lyapunov direct method and some inequality techniques, a series of novel stability criteria, which guarantee the finite-time boundedness and H∞disturbance attenuation performance of the target plants, is established in the form of spatial differential linear matrix inequalities. Finally, a simulation study is provided to verify the viability of the developed approach.",

keywords = "Asynchronous output-feedback control, Markov jump, Takagi-Sugeno fuzzy model, distributed parameter systems (DPSs), hidden Markov model (HMM)",

author = "Xiaona Song and Mi Wang and Ahn, {Choon Ki} and Shuai Song",

note = "Funding Information: Manuscript received May 7, 2019; revised July 8, 2019; accepted August 12, 2019. Date of publication September 6, 2019; date of current version August 18, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61976081 and Grant U1604146, in part by the Foundation for the University Technological Innovative Talents of Henan Province under Grant 18HASTIT019, and in part by the National Research Foundation of Korea through the Ministry of Science, ICT and Future Planning under Grant NRF-2017R1A1A1A05001325. This article was recommended by Associate Editor L. Zhang. (Corresponding author: Choon Ki Ahn.) X. Song and M. Wang are with the School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China (e-mail: xiaona_97@163.com; wangmi_17@163.com). Publisher Copyright: {\textcopyright} 2013 IEEE.",

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