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Hidden-Markov-Model-Based Asynchronous H∞ Tracking Control of Fuzzy Markov Jump Systems

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Min Xue, Huaicheng Yan, Hao Zhang, Jun Sun, Hak-Keung Lam

Original languageEnglish
Article number8967133
Pages (from-to)1081-1092
Number of pages12
JournalIEEE Transactions on Fuzzy Systems
Issue number5
PublishedMay 2021

Bibliographical note

Funding Information: Manuscript received August 19, 2019; revised November 17, 2019; accepted January 8, 2020. Date of publication January 23, 2020; date of current version May 5, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 61673178, Grant 61773289, and Grant 61922063, in part by the Shanghai International Science and Technology Cooperation Project under Grant 18510711100, in part by the Shanghai and HongKong-Macao-Taiwan Science and Technology Cooperation Project under Grant 19510760200, in part by the Shanghai Shuguang Project under Grant 18SG18, in part by the Shanghai Natural Science Foundation under Grant 17ZR1444700 and Grant 17ZR1445800, in part by the Program of Shanghai Academic Research Leader under Grant 19XD1421000, and in part by the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017. (Corresponding author: Huaicheng Yan.) M. Xue is with the School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China (e-mail: Publisher Copyright: © 1993-2012 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.


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This article is concerned with the problem of imperfect premise matching asynchronous H{infty } output tracking control for Takagi-Sugeno fuzzy Markov jump systems. A hidden Markov model is established due to the fact that the modes information of the system may not be accurately transmitted to the controller, which is used to depict the asynchronous phenomenon between the system modes and controller modes. The packet loss in the communication process is described by a stochastic variable subject to Bernoulli distribution. Then, based on a novel Lyapunov function, the mode-dependent and fuzzy-basis-dependent stability criteria are derived and the asynchronous control scheme is developed subject to an H{infty } tracking performance. Finally, two examples are provided to demonstrate the effectiveness of the proposed approach.

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