Pinning-Based Neural Control for Multiagent Systems With Self-Regulation Intermediate Event-Triggered Method

A pinning-based self-regulation intermediate event-triggered (ET) funnel tracking control strategy is proposed for uncertain nonlinear multiagent systems (MASs). Based on the backstepping framework, a pinning control strategy is designed to achieve the tracking control objective, which only uses the...

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Veröffentlicht in:IEEE transaction on neural networks and learning systems 2024-04, Vol.PP, p.1-11
Hauptverfasser: Ren, Hongru, Liu, Zeyi, Liang, Hongjing, Li, Hongyi
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Liang, Hongjing
Li, Hongyi
description A pinning-based self-regulation intermediate event-triggered (ET) funnel tracking control strategy is proposed for uncertain nonlinear multiagent systems (MASs). Based on the backstepping framework, a pinning control strategy is designed to achieve the tracking control objective, which only uses the communication weight between the agents without additional feedback parameters. Moreover, by designing a self-regulation triggered condition based on the tracking error, the intermediate triggered signal is calculated to replace the continuous signal in the controller, so as to achieve the goal of discontinuous update of the controller signal, and this mechanism does not need to add additional compensation function to the controller signal. At the same time, the funnel method is adopted to restrict the error of step n and avoid the possible negative impact caused by control signal. Furthermore, the nonlinear noncontinuous faults are compensated by the disturbance observer. Then, the Lyapunov stability theorem is used to prove that all signals of the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, some simulation results confirm the effectiveness of the proposed control scheme.
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Based on the backstepping framework, a pinning control strategy is designed to achieve the tracking control objective, which only uses the communication weight between the agents without additional feedback parameters. Moreover, by designing a self-regulation triggered condition based on the tracking error, the intermediate triggered signal is calculated to replace the continuous signal in the controller, so as to achieve the goal of discontinuous update of the controller signal, and this mechanism does not need to add additional compensation function to the controller signal. At the same time, the funnel method is adopted to restrict the error of step &lt;inline-formula&gt; &lt;tex-math notation="LaTeX"&gt;n&lt;/tex-math&gt; &lt;/inline-formula&gt; and avoid the possible negative impact caused by control signal. Furthermore, the nonlinear noncontinuous faults are compensated by the disturbance observer. 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subjects Backstepping
Event-triggered (ET) control
Multi-agent systems
multiagent systems (MASs)
neural network (NN)
nonlinear faults
pinning method
Simulation
Synchronization
Target tracking
Topology
Vectors
title Pinning-Based Neural Control for Multiagent Systems With Self-Regulation Intermediate Event-Triggered Method
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