Dynamic Event-Triggered Near Optimal Control for Solving Mixed Zero-Sum Games Via Adaptive Dynamic Programming

In this paper, we propose a dynamic event-triggered control (DETC) method that uses the adaptive dynamic programming (ADP) algorithm to address mixed zero-sum games (MZSGs). The designed method aims to optimize control strategies while reduce the consumption of communication and computational resources. Firstly, an ADP-based method is developed to address the issue of MZSGs in multi-player nonlinear systems. Secondly, by designing a dynamic-triggering condition, an ADP method using DETC strategy is proposed to reduce the waste of computing resources. The uniformly ultimately bounded (UUB) stability of the system state and neural network (NN) weight values can be guaranteed by the Lyapunov theorem. The efficacy and practicability of the developed control approach are demonstrated via case studies. Different from static event-triggering mechanisms, the simulation results present a significant reduction in the number of actuator updates, highlighting the efficiency of the proposed DETC method.