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第36届中国控制会议

作者： Lixin Wei Rui Fan Xin Li Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781538629185

Comprehensive learning particle swarm optimization（CLPSO） algorithm has a good performance in overcoming premature convergence and avoiding getting stuck in local minima, which are shortcomings in particle swarm optimization. It can solve complex, multi-modal of single-objective problems, but it has not such performance in handling multi-objective optimization problems because of the difficulty of selective solution mechanism. In this article, a multi-objective decomposition particle swarm optimization based on comprehensive learning strategy is proposed, which uses a comprehensive learning strategy for multi-objective problems to prevent premature convergence;updates the leading particles by decomposition method to enhance the distribution of solutions;adds the archive to preserve non-dominated solutions, and adopts mutation in archive to avoid falling into local optimum. The proposed approach is compared with three multi-objective evolutionary algorithms and the results indicate that the proposed approach is competitive respect to which it is compared in most of the test problems adopted.

关键词： comprehensive learning particle swarm optimization multi-objective optimization decomposition

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Friction compensation control of space manipulator considering the effects of gravity 35

Friction compensation control of space manipulator consideri...

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第35届中国控制会议

作者： QIN Li JIA Xiao-jing LIU Cai-feng LIU Fu-cai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781509009107

All space manipulators are debugged on the ground and on-orbit serviced in space. Compared with in ground gravity environment their friction characteristics in space microgravity environment have great changes. For sake of tracking the desired trajectory, in both ground and space, considering these characteristics, a friction compensation control method based on an Active Disturbance Rejection control(ADRC) is proposed and its effectiveness is validated on a planar 2-DOF free-floating space manipulator. The friction models and the dynamic models under different gravity environment have been derived based on the torque balance, the Kane equation and the Lagrange method. Particle Swarm Optimization(PSO) is put forward to optimize parameters of ADRC so as to improve the efficiency of designing process. Compared with PD controller in tracking simulation under different gravity environment, the results verify the advantage of the proposed improved control method.

关键词： space manipulator gravity friction compensation ADRC Trajectory tracking PSO

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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 study on clutch multi-modal fuzzy control in AMT vehicle starting process

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Journal of Computational Information Systems 2013年第6期9卷 2121-2129页

作者： Zang, Huaiquan Li, Dongdong Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical and Engineering Yanshan University Qinhuangdao 066004 China

In this paper, mathematical model of relationship between clutch engaging speed and engine output torque is firstly established to solve the problem of clutch engaging speed in AMT vehicle starting process, basing on analysis of the reduced kinetic model of clutch. Then multi-modal fuzzy control algorithm is adopted to precisely predict clutch engagement stage, and then driver's intension is considered to fuzzy control the clutch engaging speed. Finally, simulation modal is established. The simulation results show that, basing on the drivers intension and external environment, the control strategy proposed in this paper not only makes the vehicle start fast and stably, but also reduces slip friction work with the premise of comfort, which extends clutch working life and obtains better control performance in clutch starting process. Copyright © 2013 Binary Information Press.

关键词： Clutches

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Vibration suppress of flexible spacecraft considering the effects of gravity 34

Vibration suppress of flexible spacecraft considering the ef...

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第三十四届中国控制会议

作者： GAO Juan-juan CHEN Xin JIA Xiao-jing LIU Fu-cai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

ISBN: (纸本)9781467374439

Considering that gravity on the ground alignment phase is different from that in space application phase, an adaptive backstepping sliding mode control method is proposed to achieve the attitude control and vibration suppression of the flexible spacecraft under different gravity environment. Fully considering the change of dynamic models, the sliding mode controller is designed according to the backstepping theory to control the flexible spacecraft under the influence of model and disturbances uncertainties, and the adaptive control laws are proposed to estimate the disturbances and gravity item online. The control strategy can guarantee the stability of the system based on the Lyapunov theory. The simulation results show that the controller is effective in attitude control and vibration suppression of the flexible spacecraft under different gravity environment, and has important value for theoretical research and engineering application.

关键词： Flexible spacecraft,Gravity,Vibration suppression,Backstepping sliding mode,Adaptive

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control of epileptiform spikes based on nonlinear unscented Kalman filter

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Chinese Physics B 2014年第1期23卷 41-48页

作者：刘仙高庆李小俚 Key Lab of lndustrial Computer Control Engineering of Hebei Province Institute of Electrical Engineering Yanshan University Qinhuangdao 066004 China

A new control strategy based on nonlinear unscented Kalman filter(UKF) is proposed for a neural mass model that serves as a model for simulating real epileptiform stereo-electroencephalographic (SEEG) signals. The UKF is used as an observer to estimate the state from the noisy measurement because it has been proved to be effective for state estimation of nonlinear systems. A UKF controller is constructed via the estimated state and is illustrated to be effective for epileptiform spikes suppression of aforementioned model by numerical simulations.

关键词： unscented Kalman filter(UKF) control epileptiform spike closed-loop control neural mass model

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Visualization of flatness pattern recognition based on T-S cloud inference network

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Journal of Central South University 2015年第2期22卷 560-566页

作者：张秀玲赵亮臧佳音樊红敏 Key Laboratory of Industrial Computer Control Engineering of Hebei Province (Yanshan University) National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

Flatness pattern recognition is the key of the flatness control. The accuracy of the present flatness pattern recognition is limited and the shape defects cannot be reflected intuitively. In order to improve it, a novel method via T-S cloud inference network optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constructed with T-S fuzzy neural network and the cloud model. So, the rapid of fuzzy logic and the uncertainty of cloud model for processing data are both taken into account. What's more, GA possesses good parallel design structure and global optimization characteristics. Compared with the simulation recognition results of traditional BP Algorithm, GA is more accurate and effective. Moreover, virtual reality technology is introduced into the field of shape control by lab.VIEW, MATlab.mixed programming. And virtual flatness pattern recognition interface is ***, the data of engineering analysis and the actual model are combined with each other, and the shape defects could be seen more lively and intuitively.

关键词： pattern recognition T-S cloud inference network cloud model mixed programming virtual reality visual recognition

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A novel observer design method for neural mass models

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Chinese Physics B 2015年第9期24卷 68-72页

作者：刘仙苗东凯高庆徐式蕴 Key Laboratory of Industrial Computer Control Engineering of Hebei Province Institute of Electrical EngineeringYanshan University China Electric Power Research Institute

Neural mass models can simulate the generation of electroencephalography（EEG） signals with different rhythms,and therefore the observation of the states of these models plays a significant role in brain research. The structure of neural mass models is special in that they can be expressed as Lurie systems. The developed techniques in Lurie system theory are applicable to these models. We here provide a new observer design method for neural mass models by transforming these models and the corresponding error systems into nonlinear systems with Lurie form. The purpose is to establish appropriate conditions which ensure the convergence of the estimation error. The effectiveness of the proposed method is illustrated by numerical simulations.

关键词： observer design neural mass model Lurie system theory

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Anti-saturation fault-tolerant adaptive torsional vibration control with fixed-time prescribed performance for rolling mill main drive system

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Journal of Iron and Steel Research International 2024年第3期31卷 660-669页

作者： Shuang Liu Chen Du Cong Zhang Zhen-hua Bai Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004HebeiChina National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao 066004HebeiChina

An anti-saturation fault-tolerant adaptive torsional vibration control method with fixed-time prescribed performance for the rolling mill main drive system(RMMDS)was investigated,which is affected by control input saturation,actuator faults,sensor measurement errors,and parameter ***,we gave a continuously differentiable saturation function to approximate the control input saturation characteristic of the RMMDS,translating the saturation characteristic into the matched uncertainty and unknown time-varying gain in the ***,an RMMDS mathematical model with unmatched uncertainty and unknown time-varying gain was developed,taking into account the presence of control input saturation,actuator faults,sensor measurement errors,and parameter *** on the established mathematical model,an error transformation model of the roll speed tracking was constructed by the equivalent error transformation *** to the error transformation model,a barrier Lyapunov function and a novel adaptive controller were studied to ensure that the roll speed tracking error always evolves inside a fixed-time asymmetric ***,numerical simulations were performed in Matlab.Simulink to verify the effectiveness and superiority of the proposed control method in suppressing the RMMDS torsional vibration.

关键词： Fixed-time prescribed performance control input saturation Actuator fault Unknown time-varying gain Adaptive control Asymmetric constraint

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A new LMS algorithm with application to fixed satellite communications

A new LMS algorithm with application to fixed satellite comm...

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International Workshop on Advanced Computational Intelligence

作者： Li, Haibin Han, Yanguang Guan, Xinping Key Lab. of Industrial Computer Control Engineering Hebei Province Qinhuangdao CO 066004 China

ISBN: (纸本)9781424463343

A distinctive new LMS algorithm is proposed in his paper. Both fast convergence rate and small steady state rror can be obtained through non-linear weighting N errors of the current moment and past moments in this algorithm. The algorithm analyzed that the ideal step size is achieved by increasing the error information, building new nonlinear relations between step size factor and error function and eliminating the effect of correlated noise sequences. Then the new algorithm is applied to the fixed satellite communications system in which the channel is affected by multipath effect and weather conditions attenuation. Simulation results show that the new algorithm converges faster than usual algorithms under approximate steady state performance. The signal BER performance is greatly improved with the new adaptive algorithm equalizer in the fixed satellite communications system.

关键词： Satellite communication systems

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