Distributed control of second-order nonlinear time-delayed multiagent systems with disturbance using neural networks

In this paper, a class of second-order nonlinear time-delayed multiagent systems with disturbance is investigated. In order to improve the adaptivity, neural networks are used to learn the unknown dynamics. Then, by utilizing Lyapunov-Krasovskii functional, time delays can be eliminated. Moreover, a robustifying term is introduced to constrain external disturbance. With divide-and-conquer idea, the distributed controller is divided into five different parts to make the multiagent systems reach consensus. To circumvent the singularity induced by the time-delay elimination part, a σ-function is developed. Finally, the simulation results demonstrate the validity of the distributed controller.

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