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Integral Sliding Mode-Based Event-Triggered Nearly Optimal Tracking Control for Uncertain Nonlinear Systems
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  • Yongwei Zhang,
  • Shunchao Zhang,
  • Yonghua Wang,
  • Dacai Liu,
  • Jiawei Zhuang
Yongwei Zhang
Guangdong University of Technology School of Automation

Corresponding Author:yongwei_zhang@mail2.gdut.edu.cn

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Shunchao Zhang
Guangdong University of Finance
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Yonghua Wang
Guangdong University of Technology School of Automation
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Dacai Liu
Guangdong University of Finance
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Jiawei Zhuang
Guangdong University of Technology School of Automation
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Abstract

In this paper, an event-triggered nearly optimal tracking control method is investigated for a class of uncertain nonlinear systems by integrating adaptive dynamic programming (ADP) and integral sliding mode (ISM) control. By introducing a neural network (NN) adaptive term, the designed ISM-based discontinuous control law is employed to eliminate the influence of the uncertainties and obtain the tracking error system constructed from the sliding mode dynamics, as well as relax the known upper-bounded condition of uncertainties. In order to guarantee the stability of tracking error system and improve the control performance, under the ADP technique, a critic NN is applied to approximate the optimal value function for solving the event-triggered Hamilton-Jacobi-Bellman equation and the event-triggered nearly optimal feedback control is obtained. The feedback control law is updated and transmitted to plant only when events occur, thus both the communication and the computational resources can be saved. Furthermore, the stability of tracking error is proven thanks to Lyapunov’s direct method. Finally, we provide two simulation examples to validate the developed control scheme.
27 Jun 2023Submitted to International Journal of Robust and Nonlinear Control
27 Jun 2023Submission Checks Completed
27 Jun 2023Assigned to Editor
27 Jun 2023Review(s) Completed, Editorial Evaluation Pending
06 Jul 2023Reviewer(s) Assigned
26 Jul 2023Editorial Decision: Revise Minor
28 Sep 20231st Revision Received
30 Sep 2023Submission Checks Completed
30 Sep 2023Assigned to Editor
30 Sep 2023Review(s) Completed, Editorial Evaluation Pending
31 Oct 2023Editorial Decision: Accept