Fully Distributed Sub-Optimal Coordination for Nonlinear Multi-Agent Systems

This paper is concerned with the distributed coordination problem for the nonlinear multi-agent system (MAS) over a general digraph, where each agent is a multi-input multi-output system. The existing solutions are limited to the system without inputs coupling and with known, global Lipschitz, or linearly growing nonlinearities. To remove these requirements, we propose an integrated sub-optimal and control strategy for the more general nonlinear MAS. It consists of a fully distributed adaptive gradient optimization algorithm and a set of model-free prescribed performance controllers. Our approach ensures that the outputs of the MAS converge to the arbitrarily small neighborhoods of the optimal outputs; in particular, the reference-tracking performance is allowed to be freely predefined. Besides, the proposed control strategy is notably simple compared to the existing approaches, which typically employ function approximation, parameter identification, or derivative calculation. Finally, the simulation results illustrate the effectiveness and superiority of the proposed approach.