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• W4309223892 abstract "In this paper, we studied the cooperative control problem for a class of high-order nonlinear multi-agent systems (MASs) with external disturbance and system uncertainty. A neuro-adaptive robust controller with sliding mode variable structure method, with an online-learning RBF-like neural network was proposed to approximate the nonlinear terms. Further, sliding mode variable structure method was used to eliminate the influence of external disturbance and system uncertainty. Lyapunov stability theorem verified the capability of system consensus, and the sufficient conditions for cooperatively uniformly ultimately bounded (CUUB) are also given. At last, two numerical simulations on both homogeneous and heterogeneous MASs demonstrated the effectiveness of our proposed method." @default.
• W4309223892 created "2022-11-24" @default.
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• W4309223892 date "2022-11-15" @default.
• W4309223892 modified "2023-10-16" @default.
• W4309223892 title "Neuro-adaptive cooperative control for a class of high-order nonlinear multi-agent systems" @default.
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• W4309223892 doi "https://doi.org/10.1177/00202940221106559" @default.
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