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Active queue management of delay network based on constrained model predictive control

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4 Author(s)
Ping Wang ; Department of Control Science and Engineering, Jilin University, Changchun 130025, China ; Hong Chen ; Xiaoping Yang ; Xiaohui Lu

MPAQM algorithm is able to adapt to the varying network environment and improve the robustness by moving horizon optimization, and handling network constraints in the process of obtaining the drop probability. Based on MPAQM scheme proposed previously, the predictive model is improved to reduce the order of optimization problem in this paper. Considering the causality of time-delay system, the predicted output is defined, and the future queue length in data buffer, which is the basis of optimizing drop probability, is predicted. Furthermore, the optimal control objective and the system constraints are derived correspondingly. The simulation results show that MPAQM algorithm outperforms RED and PI algorithms in terms of stability, disturbance rejection, and robustness.

Published in:

2011 Chinese Control and Decision Conference (CCDC)

Date of Conference:

23-25 May 2011