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Neural Computing and Applications

Erschienen in:

01.12.2014 | Original Article

Research for AQM based on MiniMax method

verfasst von: Xudong Yuan, Yuanwei Jing

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2014

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Abstract

This paper proposes an active queue management (AQM) controller for a class of linearized congestion router network systems in the presence of unknown time-varying link number and disturbances. Based on the idea of MiniMax method in game theory, a novel output feedback controller is specially designed with the improved robustness to the disturbances and parameter variations. By applying the proposed algorithm in the terms of LMIs, the worst effect caused by the disturbance can be evaluated using MiniMax method, and mean while the controller is optimally designed to deal with the system under the worst condition. Finally, the effectiveness of presented AQM method is verified on the software platform of NS2.

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Titel: Research for AQM based on MiniMax method
verfasst von: Xudong Yuan
Yuanwei Jing
Publikationsdatum: 01.12.2014
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7-8/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-014-1666-1

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