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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 13/2020

31.08.2019 | Original Article

Adaptive finite-time congestion controller design of TCP/AQM systems based on neural network and funnel control

verfasst von: Kun Wang, Yuanwei Jing, Yang Liu, Xiaoping Liu, Georgi M. Dimirovski

Erschienen in: Neural Computing and Applications | Ausgabe 13/2020

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Abstract

This work investigates an adaptive finite-time congestion control problem of transmission control protocol/active queue management. By means of the funnel control, neural networks and sliding mode control, a new AQM algorithm is proposed to ensure that the tracking error \(e_{1}\left( t\right) \) converges to the prescribed boundary in finite time and the transient and steady-state performances of \(e_{1}\left( t\right) \) can be satisfied. The stability analysis is given to prove that all the signals of the closed-loop system are finite-time bounded. Finally, a comparison example is considered to demonstrate the feasibility and superiority of the presented scheme.
Vorheriger Artikel A new spatio-temporal background–foreground bimodal for motion segmentation and detection in urban traffic scenes
Nächster Artikel A new discriminative collaborative representation-based classification method via l2 regularizations

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Metadaten
Titel
Adaptive finite-time congestion controller design of TCP/AQM systems based on neural network and funnel control
verfasst von
Kun Wang
Yuanwei Jing
Yang Liu
Xiaoping Liu
Georgi M. Dimirovski
Publikationsdatum
31.08.2019
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 13/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-019-04459-4

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