Event-triggered robust adaptive critic control for nonlinear disturbed systems

A novel dynamic event-triggered control strategy is proposed by utilizing the adaptive critic learning (ACL) technique for nonlinear continuous-time systems subject to disturbances in this paper. To address the transformation of the robust-optimal control problem, a modified cost function containing the disturbance term is introduced. The dynamic event-triggered controller is obtained by incorporating an internal variable into the static triggering strategy. An ACL method is employed to design static and dynamic triggering controllers. Critic neural networks are used to approximate the cost function and the corresponding Hamilton–Jacobi–Bellman equation, leading to the establishment of adaptive critic event-triggered controllers. Stability analysis of the closed-loop system is also provided, and simulation results demonstrate the effectiveness of the developed dynamic triggering strategy with two examples.