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Dynamic Feedback Tracking Control for Interval Type-2 T-S Fuzzy Nonlinear System Based on Adaptive Event-Triggered Strategy

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Abstract

This paper explores the tracking control problem for a category of discrete-time nonlinear networked control systems (NCSs) with unknown state, parameter uncertainty, data packet dropout and time delay. Our aim is to construct a dynamic tracking feedback controller with a novel event-triggered (ET) scheme to guarantee the system output can track the reference output signal within an allowable error range. With the purpose of reducing the utilization of network resources, an improved adaptive ET communication scheme is designed at first, which can save more network resources. Secondly, the uncertainties can be easily expressed by using the interval type-2 (IT2) T-S fuzzy model to describe the nonlinear systems. Next, a dynamic feedback controller with asynchronous premise variables is designed, and the sufficient conditions for less conservative stability of the system and the design method of the controller are obtained by applying slack matrices. Finally, numerical examples are provided to further illustrate the validity of the strategy proposed in this paper.

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Acknowledgements

This work is supported in part by The Fundamental Research Funds in Heilongjiang Provincial Universities under grant 135309372, and Natural Science Foundation of Heilongjiang Province under grant LH2021F057.

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Authors and Affiliations

  1. School of Communication and Electronic Engineering, Qiqihar University, 42 Wenhua Street, Jianhua District, Qiqihar, 161006, China

    Yang Jia, Lijing Wang & Fengxia Xu

  2. School of Electronic Engineering, Heilongjiang University, 74 Xuefu Road, Nangang District, Harbin, 150080, China

    Yang Jia

  3. Department of Control Science and Engineering, Harbin Institute of Technology, Xidazhi Street, Nangang District, Harbin, 150080, China

    Guangtao Ran & Youmin Gong

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Correspondence to Yang Jia.

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Jia, Y., Ran, G., Gong, Y. et al. Dynamic Feedback Tracking Control for Interval Type-2 T-S Fuzzy Nonlinear System Based on Adaptive Event-Triggered Strategy. Neural Process Lett 55, 1715–1740 (2023). https://doi.org/10.1007/s11063-022-10960-0

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