Event-Triggered Adaptive Control for Discrete-Time Zero-Sum Games
Ziyang Wang, Qinglai Wei, Derong Liu, Yanhong Luo · 2019
In this paper, an event-triggered adaptive dynamic programming (ADP) method is developed for the discrete-time nonlinear two-player zero-sum games. First, an event-triggered ADP algorithm is presented to solve the Hamilton-Jacobi-Isaacs (HJI) equation. Then, a novel double event-triggered scheme is designed, the control inputs and the disturbance inputs will be updated only when the triggering conditions are satisfied. Therefore, the computational burden and the communication cost can be reduced. The algorithm is implemented by two neural networks, and the stability of the two-player system is proved. Finally, an example is employed to illustrate the effectiveness of the developed method.