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Fixed-time Adaptive Event-triggered Control for a Class of Uncertain Nonlinear Systems with Input Hysteresis

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  • Control Theory and Applications
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Abstract

The problem of fixed-time adaptive event-triggered control for uncertain nonlinear systems with input hysteresis is investigated. An adaptive dynamic threshold event-triggered control scheme is proposed to schedule the update of control signals and realize the online compensation of input hysteresis. Furthermore, a fixed-time adaptive event-triggered controller is proposed based on the fixed-time stability theorem. The controller can ensure that the tracking error converges into a small and adjustable set in a fixed time, and the convergence time is independent of the initial system states. Meanwhile, all the closed-loop signals are bounded, and the Zeno behavior is excluded. Finally, the feasibility of the method is verified by some simulation examples.

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Author information

Authors and Affiliations

  1. School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China

    Jianhui Wang, Chen Wang, Yushen Wu, Yonghua Li & Yongping Du

  2. School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China

    Kairui Chen

  3. School of Computer & Information, Qiannan Normal University for Nationalities, Guizhou, 558000, China

    Kairui Chen

Authors
  1. Jianhui Wang
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Correspondence to Kairui Chen.

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This work was supported in part by the Guangdong Province Basic and Applied Basic Research Fund Project under Grant 2019A1515110995, in part by the Guangzhou Science and Technology Plan Project under Grant 202002030286, in part by the Guangzhou Yangcheng Scholars Research Project under Grant 202235199, in part of the 2022 Special Fund for Science and Technology Innovation Strategy of Guangdong Province under Grant pdjh2022a0404, in part by the National Natural Science Foundation of China under Grant 62103115, in part by the Natural Science Foundation of Guangdong Province under Grants 2021A1515011636, and in part of National College Students Innovation and Entrepreneurship Training of Guangzhou University Program under Grant s202211078101. Jianhui Wang and Chen Wang are co-first authors.

Jianhui Wang received his M.S. and Ph.D. degrees from the School of Automation, Guangdong University of Technology, Guangzhou, China, in 2009 and 2019, respectively. Since 2009, he has been with the School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou. His research interests include nonlinear systems, linear systems, and intelligent control.

Chen Wang received his B.S. degree in mechanical design manufacture and automation from Yichun University, Yichun, China, in 2017. He is currently pursuing an M.S. degree in Guangzhou University, Guangzhou, China. His research interests include nonlinear systems, multiagent systems, robotics, and intelligent control.

Yushen Wu received his B.S. degree in electrical engineering and automation from Guangzhou University, Guangzhou, China, in 2021. He is currently pursuing an M.S. degree in Guangzhou University. His research interests include active disturbance rejection control (ADRC) and motor control system design.

Yonghua Li received his B.S. degree in electrical engineering and automation from Guangzhou University, Guangzhou, China, in 2021. He is currently pursuing an M.S. degree in Guangzhou University. His research interests include sliding mode control and intelligent control.

Yongping Du received her B.S. degree in mechanical design manufacture and automation from Shaoguan University, Shaoguan, Chian, in 2021. She is currently pursuing an M.S. degree in Guangzhou University. Her research interests include adaptive control, neural networks, and nonlinear systems.

Kairui Chen received his Ph.D. degree in control science and engineering from Guangdong University of Technology, Guangzhou, China, in 2017. From 2015 to 2016, he was a Visiting Scholar with the Automation and Robotics Research Institute, University of Texas at Arlington, Arlington, TX, USA. He is currently an Associate Professor with the School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, and also with the School of Computer & Information, Qiannan Normal University for Nationalities, Guizhou. His research interests include multi-agent system control, neural networks learning, adaptive control, and distributed estimation.

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Wang, J., Wang, C., Wu, Y. et al. Fixed-time Adaptive Event-triggered Control for a Class of Uncertain Nonlinear Systems with Input Hysteresis. Int. J. Control Autom. Syst. 21, 2541–2553 (2023). https://doi.org/10.1007/s12555-022-0344-9

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  • DOI: https://doi.org/10.1007/s12555-022-0344-9

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