Adaptive Critic Learning Control of Nonlinear Wind Turbine Systems via Integral Event-Triggered Scheme

This brief addresses an integral event-triggered control approach combined with an adaptive critic learning strategy of nonlinear wind turbine systems. To address the optimal control issue, an adaptive critic learning strategy is utilized to approximate the cost function and the solution of the control law. So as to further reduce communication and calculation load, an integral event-triggered scheme is utilized to decrease the releasing rate of control signal. By integrating the triggering law in traditional static event-triggered scheme, the inter-event time can be enlarged, which is proved strictly by a proposition. In addition, the closed-loop system stability and the convergence of the weights of critic neural network are proved with the aid of Lyapunov method. Finally, simulation outcomes are derived to demonstrate the merits of the integral event-triggered adaptive critic learning control approach.