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第三十届中国控制会议

作者： SU Chunjian~1,LI Quanlan~1,GUO Sumin~1,ZHANG Guangheng~1,MA Rui~2 1.College of Mechanical and Electronic Engineering,Shandong University of Science and Technology,Qingdao 266510,P.R.China 2.College of Mechanical Engineering,Yan Shan University,Qinhuangdao 066004,P.R.China

＜正＞real-time identification of material parameters is one of the most important elements in the process of intelligent bending control for quadrangle parts,the duration of real-time identification and the level of generalization accuracy would directly affect the realization of intelligent *** scheme of control system of quadrangle parts intelligent bending has been advanced in this paper by using numerical simulation,database and neural network technology synthetically in order to control the springback of sheet metal effectively,and the real-time identification of material parameters as key technology was also *** feed forward neural network of real-time identification for material performance parameters and friction coefficient of quadrangle parts was established,which could real-time identify the needed material performance parameters through the real-time monitoring variable,and predict the optimal process parameters,which has achieved the satisfactory convergence *** experiment results of quadrangle parts intelligent bending show that the network model has a higher recognition and generalization accuracy,which could satisfy the requirements of intelligent control.

关键词： Quadrangle parts Intelligent bending real-time identification

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HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE

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Journal of Electronics(China) 2009年第1期26卷 101-112页

作者： Li Jun Zhang Shunyi Lu Yanqing Yan Junrong Nanjing University of Posts and Telecommunications Nanjing 210003 China Zhejiang Wanli University Ningbo 315100 China

Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classifi- cation system, compared with the one-step Machine Learning (ML) approach.

关键词： Traffic classification Machine Learning (ML) real-time identification

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Attitude Control of Ultra-low-earth-orbit Spacecraft Based on the Rarefied Gas Parameter identification

Attitude Control of Ultra-low-earth-orbit Spacecraft Based o...

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2010亚太航空航天技术研讨会

作者： Dang Zhaohui~* Liu Hongwei Liu Qiaolin Liu Shuai College of Aerospace and Material Engineering National University of Defense Technology Changsha 410073 China

＜正＞The aerodynamic torque is the main environmental torque on the ultra-low-earth-orbit,but it cannot be used for the controlling of spacecraft until exact transcendental data about the rarefied gas parameters are *** accommodation coefficient is one of the key gas *** identification strategy based on recurrence least square is proposed in this paper to calculate the real-time accommodation coefficient,while the moment of inertia of the spacecraft is also identified using this *** be followed,a simulated ultra-low-earth-orbit spacecraft configured with control panels,which generate aerodynamic torque to stabilize the attitude of the spacecraft,is presented.A controller stabilizing the attitude from any initial orientation is developed in this ***,simulation results of a satellite with four control panels on a 200 km altitude’s orbit validated the effectiveness of the identification method.

关键词： real-time identification ultra-low-earth-orbit attitude stabilization feedback linearization LSM

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