Distributed fuzzy adaptive consensus states tracking controller for a class of nonlinear non-affine multi-agent systems with dynamic uncertainties

Abstract

This paper proposes an adaptive distributed consensus tracking protocol approach for uncertain nonlinear multi-agent systems in pure-feedback form under a directed topology where each follower is dominated by dynamic uncertainties and non-affine function of the system. By using a new intelligent variable structure controller for each follower, the provided consensus control manner solves the problem of unknown nonlinear non-affine functions of the agents. Fuzzy systems are employed both to compensate the unknown nonlinear functions obtained by recursive design procedure for followers and to use expert’s knowledge in the controller design procedure. On-line adaptation of the controller parameters, convergence of the consensus errors of the agents to zero, boundedness of all signals involved in the closed loop system, and chattering avoidance are the main characteristics of the proposed controller and the observer. Finally, to illustrate the persistency of the controller and effectiveness of this algorithm, a numerical example of a chaotic multi-agent system is investigated.

Keywords

Lyapunov stability adaptive control non-affine nonlinear system-multi-agent systems fuzzy systems

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