Observer-based event-triggered control for zero-sum games of input constrained multi-player nonlinear systems

Abstract

In this paper, an event-triggered control (ETC) method is investigated to solve zero-sum game (ZSG) problems of unknown multi-player continuous-time nonlinear systems with input constraints by using adaptive dynamic programming (ADP). To relax the requirement of system dynamics, a neural network (NN) observer is constructed to identify the dynamics of multi-player system via the input and output data. Then, the event-triggered Hamilton–Jacobi–Isaacs (HJI) equation of the ZSG can be solved by constructing a critic NN, and the approximated optimal control law and the worst disturbance law can be obtained directly. A triggering scheme which determines the updating time instants of the control law and the disturbance law is developed. Thus, the proposed ADP-based ETC method cannot only reduce the computational burden, but also save communication resource and bandwidths. Furthermore, we prove that the signals of the closed-loop system and the approximate errors of the critic NN weights are uniformly ultimately bounded by using Lyapunov’s direct method, and the Zeno behavior is excluded. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed ETC scheme.