Prescribed-time consensus of time-varying open multi-agent systems with delays on time scales (Q6595287)
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scientific article; zbMATH DE number 7903543
| Language | Label | Description | Also known as |
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| English | Prescribed-time consensus of time-varying open multi-agent systems with delays on time scales |
scientific article; zbMATH DE number 7903543 |
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Prescribed-time consensus of time-varying open multi-agent systems with delays on time scales (English)
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30 August 2024
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This study presents one innovative approach to prescribed-time leader-following consensus problems in time-varying open multi-agent systems (OMASs) with time delays. Unlike asymptotic consensus or finite-time consensus, prescribed-time consensus has provoked more public discussion due to its faster convergence rate, stronger robustness and easier operability. To solve the problem of prescribed-time consensus, the authors focus on developing a novel segmented state feedback control protocol. It is particularly commendable, as it incorporates a time-varying scalar function to ensure consensus achievement despite the uncertainty in Lyapunov function monotonicity. The introduction of impulsive signals dependent on the leader at each opening instant is a clever strategy to mitigate the risk of excessive controller norm. Furthermore, their innovative extension of Halanay-like inequalities on time scales is a critical theoretical contribution that effectively tackles the challenges posed by time delays in theoretical analysis. The integration of time scale theory and Lyapunov stability theory to derive sufficient conditions for prescribed-time consensus based on system and controller parameters is a robust analytical framework that enhances the practical applicability of the proposed approach. Additionally, the authors' consideration of incomplete agent information and the subsequent design of an observer system to reconstruct original system information demonstrates a thorough understanding of real-world constraints and the need for robust, adaptable solutions. The validation of the proposed theory through two simulation examples adds further credibility to the study. Overall, this paper offers a commendable blend of innovative methodology and rigorous theoretical analysis, while also providing practical insights relevant to multi-agent systems.
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open multi-agent systems (OMASs)
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consensus
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prescribed-time
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impulsive
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observer
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time scales
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