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Event-triggered single-network ADP method for constrained optimal tracking control of continuous-time non-linear systems

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  • Cui, Lili
  • Xie, Xiangpeng
  • Wang, Xiaowei
  • Luo, Yanhong
  • Liu, Jingbo

Abstract

This paper investigates the optimal tracking control problem (OTCP) for continuous-time non-linear systems with input constraints. A novel event-triggered single-network adaptive dynamic programming (ADP) method is proposed to obtain the solution of constrained OTCP. By constructing an augmented system and introducing a novel discounted non-quadratic cost function, an event-triggered constrained tracking Hamilton–Jacobi–Bellman equation is formulated. Then, only a critic neural network (NN) is employed to learn the optimal value function and further obtain the optimal tracking controller, which enables the architecture of ADP implementation to be simpler. And a novel NN weights updating law is constructed, by which the restriction of initial admissible control is removed. Based on the Lyapunov theory, the convergence of critic NN weights and the stability of closed-loop system are demonstrated. The derived optimal tracking controller is updated only at the event-triggered instants decided by the designed event-triggered condition. Therefore, the communication burden can be reduced effectively. Finally, two simulation examples are given to verify the effectiveness of proposed method.

Suggested Citation

  • Cui, Lili & Xie, Xiangpeng & Wang, Xiaowei & Luo, Yanhong & Liu, Jingbo, 2019. "Event-triggered single-network ADP method for constrained optimal tracking control of continuous-time non-linear systems," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 220-234.
    • Handle: RePEc:eee:apmaco:v:352:y:2019:i:c:p:220-234
    DOI: 10.1016/j.amc.2019.01.066
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    References listed on IDEAS

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    1. Wu, Li-Bing & Wang, Heng & He, Xi-Qin & Zhang, Da-Qing, 2018. "Decentralized adaptive fuzzy tracking control for a class of uncertain large-scale systems with actuator nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 390-405.
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    Cited by:

    1. Wang, Wei & Xie, Xiangpeng & Feng, Changyang, 2022. "Model-free finite-horizon optimal tracking control of discrete-time linear systems," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    2. Wang, Xianming & Shen, Mouquan, 2023. "Model free optimal control of unknown nonaffine nonlinear systems with input quantization and DoS attack," Applied Mathematics and Computation, Elsevier, vol. 448(C).
    3. Cui, Lili & Zhang, Yong & Wang, Xiaowei & Xie, Xiangpeng, 2021. "Event-triggered distributed self-learning robust tracking control for uncertain nonlinear interconnected systems," Applied Mathematics and Computation, Elsevier, vol. 395(C).
    4. Zhao, Yanwei & Wang, Huanqing & Xu, Ning & Zong, Guangdeng & Zhao, Xudong, 2023. "Reinforcement learning-based decentralized fault tolerant control for constrained interconnected nonlinear systems," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).

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