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- W2972090218 abstract "In this article, we consider the leader-follower consensus control problem of uncertain multiagent systems, aiming to achieve the improvement of system steady state and transient performance. To this end, a new adaptive neural control approach is proposed with a novel design of the Lyapunov function, which is generated with a class of positive functions. Guided by this idea, a series of smooth functions is incorporated into backstepping design and Lyapunov analysis to develop a performance-oriented controller. It is proved that the proposed controller achieves a perfect asymptotic consensus performance and a tunable L <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>2</sub> transient performance of synchronization errors, whereas most existing results can only ensure the stability. Simulation demonstrates the obtained results." @default.
- W2972090218 created "2019-09-12" @default.
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- W2972090218 date "2021-01-01" @default.
- W2972090218 modified "2023-10-14" @default.
- W2972090218 title "Adaptive Consensus Tracking Control of Uncertain Nonlinear Multiagent Systems With Predefined Accuracy" @default.
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- W2972090218 doi "https://doi.org/10.1109/tcyb.2019.2933436" @default.
- W2972090218 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31484149" @default.
- W2972090218 hasPublicationYear "2021" @default.
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