Event-triggered Control for Zero-sum Games Based on Critic-identifier Architecture with Particle Swarm Optimization

Abstract

In this paper, an event-triggered control (ETC) scheme for zero-sum game problems is proposed. To solve the Hamilton-Jacobi-Isaacs equation of the unknown nonlinear system, the adaptive dynamic programming method with critic-identifier architecture is utilized. In order to train the neural networks (NN) more efficiently and avoid manually selecting the corresponding initial weights, the particle swarm optimization is employed. In addition, the actuator is updated aperiodically under the event-triggered framework, thus, reducing the computational burden and saving communication resources to some extend. A novel triggering rule, which can guarantee the closed-loop system to be uniformly ultimately bounded, is developed through the Lyapunov method. Finally, the effectiveness of the proposed ETC scheme is demonstrated via a simulation study.