Online event-triggered adaptive critic design for non-zero-sum games of partially unknown networked systems

Abstract

In this work, an event-triggered adaptive control scheme is proposed for the multi-player non-zero-sum (NZS) games of the nonlinear continuous-time networked systems with partially unknown dynamics. A fuzzy logic model (FLM)-based identifier is established to reconstruct the unknown system dynamics. To obtain the approximate Nash equilibrium solution, the critic neural networks (NN) are utilized to approximate the value functions and the control policies. Different from the classical event-based methods, a novel state-dependent event triggering condition is derived to reduce the recomputations and communications of the system input signals and to guarantee the control stability in the meanwhile. Moreover, by the means of the Lyapunov theorem, the uniform ultimate boundedness (UUB) properties of the system state and the critic NN weight estimation errors are proved. Finally, the theoretical analysis is substantiated by two numerical examples.