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Neural Computing and Applications

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01-12-2014 | Original Article

Research for AQM based on MiniMax method

Authors: Xudong Yuan, Yuanwei Jing

Published in: Neural Computing and Applications | Issue 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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Title: Research for AQM based on MiniMax method
Authors: Xudong Yuan
Yuanwei Jing
Publication date: 01-12-2014
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 7-8/2014
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-014-1666-1

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