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Adaptive neural network consensus tracking control for uncertain multi-agent systems with predefined accuracy
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DOI：10.1007/s11071-020-05885-z.png)
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Abstract
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This paper proposes the consensus tracking control problem for a class of uncertain nonlinear multi-agent systems. By using a group of nonnegative functions, an adaptive neural network controller is addressed based on the technique of backstepping. Compared with existing results about uncertain nonlinear multi-agent systems, the advantage of the proposed scheme is that it can ensure the consensus of multi-agent systems within a given accuracy by using twonth-order continuous differentiable functions. Finally, simulation results confirm the correctness of the proposed scheme.
Keywords:
Nonlinear multi-agent systems
Adaptive neural network control
Consensus tracking control
Predefined accuracy
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