Integral reinforcement learning-based guaranteed cost control for unknown nonlinear systems subject to input constraints and uncertainties

Highlights：

• Secondly, inspired by Vrabie and Lewis (2009)[35] and Liu et al. (2020)[36], the proposed control method is presented to drive an event-based H∞ control policy by applying RL algorithm without requiring a stable initial control law, which is necessary in the implemen-tation of event-triggered RL-based control approaches developed in Adib and Braun (2019)[25], Liu et al. (2019)[29], Wang et al. (2019)[33] and Vrabie et al. (2009)[34].

• Thirdly, since the phenomenon of input constraints often exists in nonlinear practical control systems, different from Liu et al. (2019)[29], Liu et al. (2021)[37], Han et al. (2020)[38] and Liu et al. (2020)[39], the event-triggered H∞ control strategies is developed for nonlinear system dynamics subject to actuator failures.

摘要

•Firstly, a novel FTC strategy involved with event-triggered mechanism and ISMC method is proposed for nonlinear systems subject to actuator failures. The proposed control method can make the nonlinear systems stable, as well as lower the frequency of network communication of the controlled systems, and therefore avoid the waste of system resources.•Secondly, inspired by Vrabie and Lewis (2009)[35] and Liu et al. (2020)[36], the proposed control method is presented to drive an event-based H∞ control policy by applying RL algorithm without requiring a stable initial control law, which is necessary in the implemen-tation of event-triggered RL-based control approaches developed in Adib and Braun (2019)[25], Liu et al. (2019)[29], Wang et al. (2019)[33] and Vrabie et al. (2009)[34].•Thirdly, since the phenomenon of input constraints often exists in nonlinear practical control systems, different from Liu et al. (2019)[29], Liu et al. (2021)[37], Han et al. (2020)[38] and Liu et al. (2020)[39], the event-triggered H∞ control strategies is developed for nonlinear system dynamics subject to actuator failures.