Distributed Adaptive Consensus Control and Disturbance Suppression of Unknown Nonlinear Multi-Agent Systems

This paper considers consensus control of unknown nonlinear multi-agent systems with unknown disturbance under undirected networks. The expected output signal of the leader is not available to all subsystems, only some subsystems can obtain it, and other subsystems will obtain the output regulation error through the network connections. The critical contribution of this paper is to develop a new distributed adaptive control protocol and disturbance observer based on relative output information to achieve the consensus control objective of the subsystems. Since only the relative output information is used, the adaptive control protocol we proposed is distributed. Also, a new lemma is proposed for the first time to analyze the stability of the subsystems. Comparing to current results, the challenge exists in this paper is that the external disturbance is unknown and does not have explicit expression. Based on this, designing a disturbance observer based on relative output information to achieve consensus output regulation is the motivation of this paper. Different from the existing disturbance suppression methods, only the relative output information is used for disturbance suppression, and only the part of disturbance that affects the common trajectory will be suppressed. The stability analysis of the systems is carried out by using algebraic graph theory, Lyapunov function, and Barbalat lemma. The outcome of the paper is that all variables of the systems are bounded and the output regulation errors of the subsystems converge to zero asymptotically. Finally, a numerical simulation is given to demonstrate the effectiveness of the proposed method.