Journal Article10.1109/TNNLS.2020.3009098
Neural-Network-Based Fully Distributed Adaptive Consensus for a Class of Uncertain Multiagent Systems
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TL;DR: This article revisits the problem of distributed neuroadaptive consensus for uncertain multiagent systems (MASs) in the presence of unmodeled nonlinearities as well as unknown disturbances and proposes a robust consensus controllers comprising a linear feedback term, a discontinuous feedbackterm, and a neural network approximation term.
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Abstract: In this article, we revisit the problem of distributed neuroadaptive consensus for uncertain multiagent systems (MASs) in the presence of unmodeled nonlinearities as well as unknown disturbances. Robust consensus controllers comprising a linear feedback term, a discontinuous feedback term, and a neural network approximation term are constructed, where in each term, the weight part is endowed with some dynamical changing law. The asymptotic convergence of the consensus errors is theoretically proved based on the graph theory, nonsmooth analysis, and Barbalat’s lemma. Both leaderless consensus and leader–follower tracking problems are considered before the results are further extended to containment problem in the presence of multileaders. A dramatic feature of the proposed method, in comparison with related works, is the fully distributed fashion of the information, requiring neither the underlying Laplacian eigenvalues nor the input upper bounds of the leaders (if exist). Several numerical examples are presented to testify the theoretical results.
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Citations
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Leader tracking control for heterogeneous uncertain nonlinear multi-agent systems via a distributed robust adaptive PID strategy
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TL;DR: In this paper , the tracking control problem for a class of nonlinear multi-agent systems (MASs) is researched by the combination of radial basis function neural networks (RBF NNs) and an improved dynamic surface control (DSC) technology.
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Bipartite Tracking Consensus for High-Order Heterogeneous Uncertain Nonlinear Multi-Agent Systems With Unknown Leader Dynamics via Adaptive Fully-Distributed PID Control
TL;DR: Based on the Lyapunov theory, this paper derived adaptive mechanisms able to guarantee the robust asymptotic convergence of the overall networked system and the boundedness of the time-varying control signals.
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Neural-networks-based event-triggered consensus tracking control for nonlinear MASs with DoS attacks
Yang Xiao,Wei-Wei Che +1 more
TL;DR: In this article , an observer based on neural networks (NNs-observer) is introduced to estimate unavailable system states and a new secure distributed controller is designed to achieve the tracking control objective while maintaining the tolerance to DoS attacks.
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