Event-Triggered Near Optimal Output Feedback Control for Constrained Discrete-Time Systems Via an Iterative Adaptive Algorithm

For event-triggered optimal control problems of general nonlinear systems, it is very difficult to obtain the optimal analytical solution. In this paper, an adaptive near optimal output feedback control method is presented for discrete-time (DT) nonlinear systems. The event-triggered mechanism is introduced to significantly reduce the execution costs through aperiodic control updating intervals without affecting system responses. Furthermore, an integral term is presented in the performance index function to achieve the optimal constrained control. Consequently, iterative dual heuristic dynamic programming algorithm (DHP) is adopted to learn the optimal control law and the costate function. Finally, two examples are provided to illustrate the effectiveness of the proposed approach.