Neuroadaptive consensus tracking control of uncertain nonlinear multiagent systems with state time-delays

The consistency issue of uncertain nonlinear multiagent systems with state delay is investigated. We propose a novel neuroadaptive control scheme that utilizes the novel Lyapunov-Krasovskii functional design to get rid of the effect of state delay. In the design of Lyapunov-Krasovskii functional, a set of reduced-order smoothing functions is introduced to enhance the system's transient performance. In addition, an improved tuning function method is proposed to reduce the dimension of the adaptive parameters. In this paper, the estimation parameters are the greatest norm of the ideal weighted vector, so that each agent needs only one online update parameter, which greatly reduces the online computation burden. The proposed controller converges the synchronization error to a predetermined interval and guarantees the transient performance of the adjustable L₂-norm. Finally, the results are proved through two examples.