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Neural Computing and Applications

Erschienen in:

21.07.2021 | Original Article

Event-triggered network congestion control of TCP/AWM systems

verfasst von: Yun Bai, Yuanwei Jing

Erschienen in: Neural Computing and Applications | Ausgabe 22/2021

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Abstract

For the nonlinear TCP/AWM network congestion control system with external disturbances, under the framework of backstepping control method, an adaptive network congestion control strategy based on event-triggered mechanism is proposed. This strategy reduces the waste of network resources by introducing an event-triggered mechanism and uses RBF neural network to deal with external disturbances. The Lyapunov theory is used to prove that all signals in the closed-loop system are bounded. Finally, the proposed method is verified by simulation and is compared with PID, which further verifies the effectiveness of the proposed control method.

Vorheriger Artikel SHIBR—The Swedish Historical Birth Records: a semi-annotated dataset

Nächster Artikel Event-triggered fixed-time adaptive neural tracking control for stochastic non-triangular structure nonlinear systems

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Titel: Event-triggered network congestion control of TCP/AWM systems
verfasst von: Yun Bai
Yuanwei Jing
Publikationsdatum: 21.07.2021
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 22/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-021-06209-x

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