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Chinese control Conference (CCC)

作者： Yehong Li Yiming Fang Jianxiong Li Shengli Shi Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Qinhuangdao Qinhuangdao China

For the problems of parameters change abruptly and input saturation of the rolling mill hydraulic servo systems, an adaptive backstepping control method based on multi-model switching is presented in this paper. Firstly, multiple models of the rolling mill hydraulic servo systems under different operating modes are established. Secondly, an auxiliary system is introduced to reduce the effects of input saturation, and the adaptive backstepping controllers are designed for all subsystem. With the help of common Lyapunov theory, the proposed method can guarantee stability of the multi-model switched system under arbitrary switching strategy. Finally, the simulation results demonstrate the effectiveness of the proposed control method.

关键词： Servomotors Switches Backstepping Adaptive systems Valves Actuators

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Stochastic predictive control for energy-efficient cooperative wireless cellular networks

Stochastic predictive control for energy-efficient cooperati...

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IEEE International Conference on Communications (ICC)

作者： Shuhuan Wen F. Richard Yu Jinsong Wu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Department of Systems and Computer Engineering Carleton University Ottawa ON Canada Bell Laboratories Shanghai P.R. China

Energy efficiency has become an increasingly important aspect of wireless communications. Coordinated multipoint (CoMP) processing may be considered as a promising approach to improve the energy efficiency, extend the cell coverage, and increase the communication capacity in wireless cellular networks. However, the CoMP communication systems may require a large amount of channel state information (CSI) feedbacks which would be constrained by the wireless backhaul networks. This paper proposes a control theoretical approach to improve the energy efficiency in cooperative wireless cellular networks with CoMP communications. In particular, we propose a stochastic predictive control algorithm to achieve energy-efficient CoMP transmissions through optimal base station grouping. Moreover, since the channel state information in CoMP is often outdated/lost due to the feedback delays in the backhaul network, our proposed approach is based on a new discrete time predictive function control model to mitigate the impacts of packet delay or loss of channel state information. Simulation results show the effectiveness of the proposed scheme.

关键词： Base stations Wireless communication Channel state information Delays Predictive models Predictive control Prediction algorithms

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The improved load balance adjustor of multi-motor driving system

The improved load balance adjustor of multi-motor driving sy...

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Chinese control Conference (CCC)

作者： Jing Ming Yang Bo Su Jin Lv Hai Jun Che Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China Tian Jin Design and Research Institute of Electric Drive Tianjin 300180 China

Multi-motor coaxial connected are used to drive large mechanical load motor drive system. Multi-motor driver's main advantage is can reduce the rotational inertia of the load, increase the rapidity of system, but followed by many motor driver control difficulty increase. Based on one tandem mill motor drive as the background, analyzes the series motor drive a rack rolling work mode, aiming at the load problem of this way of driving motor, design a new kind of load balance adjustor. Using load observer to get the actual load as the load balance adjustor's input, the new control method of quadratic performance indicators single neuron adaptive PID, and joined the feed forward compensation to inhibit speed fluctuations. The results show that, this method can substantially ensure the roll motor load balance, while having a good control effect.

关键词： Observers Neurons Motor drives MATlab Design methodology Channel hot electron injection Digital control

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Reliability Optimization of Multi-state Hydraulic System Based on T-S Fault Tree and Extended PSO Algorithm

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IFAC Proceedings Volumes 2013年第5期46卷 463-468页

作者： Chengyu Yao Bin Wang Dongning Chen Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China (Tel: ***) Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control Yanshan University Qinhuangdao China Key Laboratory of Advanced Forging & Stamping Technology and Science (Yanshan University) Ministry of Education of China Qinhuangdao China

In order to overcome the difficulty of constructing the multi-state system's reliability optimization model, and the shortage of premature convergence of PSO (Particle Swarm Optimization) algorithm, a new reliability optimization method based on T-S fault tree and EPSO (Extended PSO) algorithm is proposed. According to the T-S fault tree and T-S rules of the events, the multi-state system reliability optimization model is constructed, at the same time, given constraint conditions on the system cost, weight and volume, and combined with the death penalty to construct the fitness function. Furthermore, EPSO algorithm based on the attraction and repulsion forces in the artificial physics is applied to the reliability optimization of multi-state hydraulic system. Comparing with PSO algorithm, the results of EPSO algorithm are in a better performance in obtaining global optimal solution.

关键词： Hydraulic system Reliability optimization Multi-state T-S fault tree EPSO algorithm

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Reliability Prediction Method of Hydraulic System by Fuzzy Theory

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IFAC Proceedings Volumes 2013年第5期46卷 457-462页

作者： Dongning Chen Chengyu Yao Zhongkui Feng Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control Yanshan University Qinhuangdao China (Tel: ***) Key Laboratory of Advanced Forging & Stamping Technology and Science (Yanshan University) Ministry of Education of China Qinhuangdao China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

The hydraulic system's reliability is a key factor to ensure the reliable operation of equipment and it is very important to evaluate reliability of hydraulic system. The paper describes a reliability prediction method that may be used to evaluate the reliability of hydraulic systems for industrial applications. The proposed method takes advantage of fuzzy set theory. The aim of this method is to minimize the deficiencies of the traditional reliability prediction methods treating a failure rate as fixed value due to insufficiency practice data. Triangular fuzzy number and Gaussian fuzzy number are used in the application of this prediction method, where environmental factor, derating factor, and other factors are considered. Finally, an example of type crane's hydraulic system is given to verify the feasibility and practicability of the method.

关键词： Type crane Hydraulic system Reliability prediction Fuzzy theory Reliability logic diagram

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Tension control Study in the Finishing Mill of Aluminum Hot Rolling Mills based on PSO+CMAC

Tension Control Study in the Finishing Mill of Aluminum Hot ...

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2013 3rd International Conference on Advanced Measurement and Test(AMT 2013)

作者： YANG Jing-ming CHEN Li Wang Wan-hong CHE Hai-jun Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of C.S.R Yanshan University Henan Mingtai Al.Industrial Co.Ltd of

Aimed at decreasing the tension variation during transforming process of "1+4" aluminum hot rolling mills unit in one factory of Henan,we analyzed the factors affecting tension variation and improved the tension formula of hot rolling mills process considering the influence of tension on forward slip *** tension forming process of hot rolling mills from stand 1 to stand 4 is simulated,and the tension structure diagrams of the four-stands are *** to nonlinear characteristics of the aluminum hot rolling mills tension system,conventional PID controller could not meet the requirement of the *** we proposed the mixed control of Cerebellar Model Articulation controller(CMAC)coupled with PID to solve the problem of online parameters control and we used Particle Swarm Optimization(PSO)algorithm to optimize PID controller *** simulation,it could be found that the using of PSO+CMAC significantly reduced surplus adjustment and transition time,and strip tension coupling degree among stands was also reduced.

关键词： aluminum hot rolling mills tension model tension influence coefficient PSO CMAC

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Design of Robotic Visual Servo control Based on Neural Network and Genetic Algorithm

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International Journal of Automation and computing 2012年第1期9卷 24-29页

作者： Hong-Bin Wang Mian Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical EngineeringYanshan UniversityQinhuangdao 066004PRC

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.

关键词： Visual servo image Jacobian back propagation （BP） neural network genetic algorithm robot control

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A Novel Method for Flatness Pattern Recognition via Least Squares Support Vector Regression

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Journal of Iron and Steel Research International 2012年第3期19卷 25-30页

作者： ZHANG Xiu-ling, ZHANG Shao-yu, TAN Guang-zhong, ZHAO Wen-bao (key laboratory of industrial computer control engineering of hebei province, National engineering Research Center for Equipment and Technology of Cold Strip Rolling, Yanshan University, Qinhuangdao 066004, hebei, China) Key Laboratory of Industrial Computer Control Engineering of Hebei Province National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan University Qinhuangdao 066004 Hebei China

To adapt to the new requirement of the developing flatness control theory and technology, cubic patterns were introduced on the basis of the traditional linear, quadratic and quartic flatness basic patterns. Linear, quadratic, cubic and quartic Legendre orthogonal polynomials were adopted to express the flatness basic patterns. In order to over- come the defects live in the existent recognition methods based on fuzzy, neural network and support vector regres- sion （SVR） theory, a novel flatness pattern recognition method based on least squares support vector regression （LS-SVR） was proposed. On this basis, for the purpose of determining the hyper-parameters of LS-SVR effectively and enhan- cing the recognition accuracy and generalization performance of the model, particle swarm optimization algorithm with leave-one-out （LOO） error as fitness function was adopted. To overcome the disadvantage of high computational complexity of naive cross-validation algorithm, a novel fast cross-validation algorithm was introduced to calculate the LOO error of LDSVR. Results of experiments on flatness data calculated by theory and a 900HC cold-rolling mill practically measured flatness signals demonstrate that the proposed approach can distinguish the types and define the magnitudes of the flatness defects effectively with high accuracy, high speed and strong generalization ability.

关键词： flatness pattern recognition least squares support vector regression cross-validation

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Object Tracking Method Based on SURF

Object Tracking Method Based on SURF

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2012 Conference on Modelling, Identification and control (MIC2012)

作者： Hu Shuo Wu Na Song Huajun Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical EngineeringYanshan University Key Lab of Measurement Technology & Instrumentation of Hebei Province Institute of Electrical EngineeringYanshan University Institute of Information and Control Engineering China University of Petroleum(East China)

ISBN: (纸本)9781627483766

An object tracking algorithm based on SURF is presented in this *** points are detected by SURF detector in reference region which is located in the first frame *** the following sequences,the SURF feature points are extracted in a larger window which is selected as test *** the matching stage,we calculate the Euclidean distance between the descriptor vectors of interest points in the test image and ones in the reference *** proposed algorithm is implemented on an embedded platform with TI's DM6446 high performance *** experimental results show that our system implements a real-time tracking with robustness against appearance variations,scale change,and cluttered scenes.

关键词： Object track SURF descriptor feature detection DM6446

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Corrigendum to “Development and investigation of efficient artificial bee colony algorithm for numerical function optimization” [Appl. Soft Comput. 12 (2012) 320–332]

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Applied Soft Computing 2013年第4期13卷 2143-2143页

作者： Guoqiang Li Peifeng Niu Xingjun Xiao Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

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