%0 Journal Article
%T Improved disturbance observer-based fixed-time adaptive neural network consensus tracking for nonlinear multi-agent systems.
%A Zhang N
%A Xia J
%A Park JH
%A Zhang J
%A Shen H
%J Neural Netw
%V 162
%N 0
%D May 2023 17
%M 36972649
%F 9.657
%R 10.1016/j.neunet.2023.03.016
%X This paper is concerned with the problem of fixed-time consensus tracking for a class of nonlinear multi-agent systems subject to unknown disturbances. Firstly, a modified fixed-time disturbance observer is devised to estimate the unknown mismatched disturbance. Secondly, a distributed fixed-time neural network control protocol is designed, in which neural network is employed to approximate the uncertain nonlinear function. Simultaneously, the technique of command filter is applied to fixed-time control, which circumvents the "explosion of complexity" problem. Under the proposed control strategy, all agents are enable to track the desired trajectory in fixed-time, and the consensus tracking error and disturbance estimation error converge to an arbitrarily small neighborhood of the origin, meanwhile, all signals in the closed-loop system remain bounded. Finally, a simulation example is provided to validate the effectiveness of the presented design method.