Estimator-based adaptive neural network control of leader-follower high-order nonlinear multiagent systems with actuator faults

Zhou, N., Chen, R., Xia, Y. & Huang, J. 10-Jul-2017 In : Concurrency and Computation: Practice and Experience.

Research output: Scientific - peer-reviewArticle

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  • Estimator-based adaptive neural network control of leader-follower

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The problem of distributed cooperative control for networked multiagent systems is investigated in this paper. Each agent is modeled as an uncertain nonlinear high-order system incorporating with model uncertainty, unknown external disturbance, and actuator fault. The communication network between followers can be an undirected or a directed graph, and only some of the follower
agents can obtain the commands from the leader. To develop the distributed cooperative control algorithm, a prefilter is designed, which can derive the state-space representation to a newly constructed plant. Then, a set of distributed adaptive neural network controllers are designed by making certain modifications on traditional backstepping techniques with the aid of adaptive control, neural network control, and a second-order sliding mode estimator. Rigorous
proving procedures are provided,which show that uniform ultimate boundedness of all the tracking errors can be achieved in a networked multiagent system. Finally, a numerical simulation is carried out to evaluate the theoretical results.
Original languageEnglish
JournalConcurrency and Computation: Practice and Experience
StateE-pub ahead of print - 10-Jul-2017

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