Adaptive dynamic event–triggered distributed optimal coordination of heterogeneous uncertain nonlinear multiagent systems

Abstract

This paper addresses the distributed optimal coordination problem for a class of heterogeneous uncertain nonlinear multiagent systems. Instead of relying on the analytical forms of gradient functions, we use the measured gradient values depending on agents’ real-time outputs and propose a novel adaptive distributed control scheme. This scheme integrates event-triggered optimal coordinators, high-order filters, and tracking controllers. To handle the interaction between optimal coordinators and filters, we incorporate a new compensation term into the updating law for the coupling weight of each edge. Moreover, we design a novel adaptive distributed dynamic event-triggering mechanism that ensures that the inter-event times of each agent are lower bounded by a positive constant. Asymptotic convergence of agents’ outputs to the optimal point is proved by constructing a composite Lyapunov function. The proposed control scheme does not depend on global topology information. A numerical example is given to demonstrate the effectiveness of the proposed control scheme.