Practical output consensus control of uncertain nonlinear multi‐agent systems without using the higher‐order states of neighbours

Abstract

Currently, most existing consensus methods require each agent to access the higher-order states of its neighbouring agents, thereby increasing communication and computation costs in a multi-agent system. This work considers the practical consensus problem without such requirements for multi-agent systems in a strict-feedback form. Specifically, this study addresses the distributed control problem with asymmetric time-varying output constraints under a general communication topology that contains a directed spanning tree. One salient feature of this work is to present a new dynamic reference output for dealing with both the directed topology and the satisfaction of the output constraints. Based on this reference output, a distributed consensus scheme is developed such that each agent utilizes only its states and the output information of its neighbours to update the control input. The proposed method is straightforward to implement because the complex analytic computation of the derivatives of the virtual controllers is not needed. Theoretical and simulation verifications of the proposed scheme, ensuring that output consensus can be achieved without violation of the constraints and that all closed-loop signals remain bounded, are rigorously studied. KEYWORDS adaptive control, distributed consensus control, higher-order nonlinear systems, multi-agent systems 1 INTRODUCTION The last decade has witnessed many exciting developments in the area of distributed control of multi-agent systems. A distributed consensus control strategy, according to which all agents strive to reach a common final state based only on local interactions, has become an important direction due to practical needs and theoretical difficulties [1-3]. The primary methods have mainly been focused on the consensus of single-and double-order multi-agents without regarding system uncertainties [1, 4, 5]. For a more practical consideration, these developments have been applied to multi-agent systems governed by This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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