Event-triggered reinforcement learning H∞ control design for constrained-input nonlinear systems subject to actuator failures

• Published in: Information sciences Vol. 543; pp. 273 - 295
• Main Authors: Liang, Yuling, Zhang, Huaguang, Duan, Jie, Sun, Shaoxin
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 08.01.2021
• Subjects: [formula omitted] fault-tolerant control; Event-triggered control; Neural network; Reinforcement learning; Sliding mode control; Neural network; Event-triggered control; Sliding mode control; Reinforcement learning; H∞ fault-tolerant control

In the paper, a novel input-constrained H∞ fault-tolerant control approach is developed by using sliding mode control technology and event-triggered reinforcement learning (RL) algorithm. To reduce or even eliminate the impacts of the time-varying actuator failures, a properly sliding mode control s...