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- W4327717025 abstract "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." @default.
- W4327717025 created "2023-03-18" @default.
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- W4327717025 date "2023-05-01" @default.
- W4327717025 modified "2023-10-18" @default.
- W4327717025 title "Improved disturbance observer-based fixed-time adaptive neural network consensus tracking for nonlinear multi-agent systems" @default.
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- W4327717025 doi "https://doi.org/10.1016/j.neunet.2023.03.016" @default.
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