期刊
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
卷 50, 期 9, 页码 3145-3157出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2018.2853089
关键词
Robustness; Optimal control; Nonlinear systems; Robust control; Perturbation methods; Adaptive systems; Adaptive critic designs (ACDs); adaptive dynamic programming (ADP); event-triggered control (ETC); input constraints; neural network (NN); reinforcement learning (RL)
资金
- National Natural Science Foundation of China [61503379]
- China Scholarship Council under the State Scholarship Fund
- National Science Foundation [CMMI 1526835, ECCS 1731672]
In this paper, we study the event-triggered robust stabilization problem of nonlinear systems subject to mismatched perturbations and input constraints. First, with the introduction of an infinite-horizon cost function for the auxiliary system, we transform the robust stabilization problem into a constrained optimal control problem. Then, we prove that the solution of the event-triggered Hamilton-Jacobi-Bellman (ETHJB) equation, which arises in the constrained optimal control problem, guarantees original system states to be uniformly ultimately bounded (UUB). To solve the ETHJB equation, we present a single network adaptive critic design (SN-ACD). The critic network used in the SN-ACD is tuned through the gradient descent method. By using Lyapunov method, we demonstrate that all the signals in the closed-loop auxiliary system are UUB. Finally, we provide two examples, including the pendulum system, to validate the proposed event-triggered control strategy.
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