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Neural Computing and Applications

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10.07.2020 | Original Article

Robust finite-time \(H_{\infty }\) congestion control for a class of AQM network systems

verfasst von: Kun Wang, Xiaoping Liu, Yuanwei Jing

Erschienen in: Neural Computing and Applications | Ausgabe 8/2021

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Abstract

This work investigates a finite-time \(H_{\infty }\) robust congestion control issue for transmission control protocol network systems. By means of the backstepping technique, finite-time control method and \(H_{\infty }\) control theory, a novel robust \(H_{\infty }\) finite-time controller design approach is presented to guarantee the finite-time convergence of the queue tracking error. Furthermore, the closed-loop network system has an \(L_{2}\) gain less than or equal to a given positive real number. Comparative simulation results show that the proposed control method performs better than the existing control approach.

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Titel: Robust finite-time congestion control for a class of AQM network systems
verfasst von: Kun Wang
Xiaoping Liu
Yuanwei Jing
Publikationsdatum: 10.07.2020
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 8/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-020-05168-z

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