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Neural-based self-tuning controller for AQM Router Supporting TCP with ECN

Neural-based Self-tuning Controller for AQM Router Supportin...

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第25届中国控制会议

作者： Zhu Ruijun College of Informatics,Dalian Univ. of Technology,Dalian, 116023,China

＜正＞As an enhancement mechanism for the end-to-end congestion control,active queue management （AQM） can keep smaller queuing delay and higher throughput by purposefully dropping the packets at the intermediate routers. Comparing with RED algorithm, although the PI （Proportional -Integral） or PID（Proportional-Integral-differential） controller for AQM improves the stability,It is very difficulty in selecting a group of the parameters of the controller to guarantee the transient performance. Moreover,the case is even worse especially in rapidly changing and complex conditions , such as stochastically accessed users, unpredicted nonresponsive traffic and hard limitations on the network resources. In this paper,we propose a self-tuning controller for AQM router supporting TCP with ECN based on neural compensator. The effectiveness of integrated performance of the controller is demonstrated by the simulation results.

关键词： self-tuning controller AQM router neural networks

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Design of the Optimal self-tuning Fuzzy-Pi controller for Rectifier Current Control in HVDC System

Design of the Optimal Self-tuning Fuzzy-Pi Controller for Re...

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第25届中国控制会议

作者： Tacchon Ahn Wonkwang University Ik-San 570749 Korea

＜正＞In this paper, we study an approach to design a self-tuning Fuzzy-Pi controller in HVDC（High Voltage Direct Current） system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-Pi controller for the fire angle control of rectifier. The performance of the Fuzzy-Pi controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing（Genetic Algorithms, GAs）. Then we can obtain the optimal scaling factors of the Fuzzy-Pi controller by Genetic Algorithms. In order to improve Fuzzy-Pi controller, we adopt FIS to tune the scaling factors of the Fuzzy-Pi controller on line. A comparative study has been performed between Fuzzy-Pi and self-tuning Fuzzy-Pi controller, to prove the superiority of the proposed scheme.

关键词： Fuzzy-Pi controller self-tuning controller HVDC Genetic Algorithms(GAs)

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