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11th International Conference on Natural Computation, ICNC 2015

作者： Li, Xia Niu, Peifeng Li, Guoqiang Liu, Jianping Hui, Huihui Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066000 China College of Mathematics and Information Technology Hebei Normal University of Science and Technology Qinhuangdao066000 China

ISBN: (纸本)9781467376792

The Teaching-Learning-Based Optimization(TLBO) algorithm does not require special parameters setting for working the algorithm, but there are some shortcomings such as slow convergence speed and long running time. Therefore, some improvements have been done on the TLBO algorithm in the paper. Firstly, the population initialization of the TLBO algorithm is random, which does not ensure the uniform distribution of initial solutions in the solution space, and then it will affect the algorithm's efficiency to some extent. Therefore, the paper proposes opposing-based learning to initialize and renewal the population of the TLBO algorithm. Secondly, to efficiently speed up the convergence speed of the algorithm, a linear decreasing inertia weight (DIW) strategy and two nonlinear DIW strategies (a parabola opening upwards and a parabola opening downwards curve) are combined with the TLBO respectively. Finally, improved TLBO algorithms have been evaluated by 13 benchmark functions. The experimental results show that improved TLBO algorithms have much better optimization performances than the TLBO algorithm on most benchmark functions. © 2015 IEEE.

关键词： Learning algorithms

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Fuzzy adaptive robust control for space robot considering the effect of the gravity

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Chinese Journal of Aeronautics 2014年第6期27卷 1562-1570页

作者： Qin Li Liu Fucai Liang Lihuan Gao Jingfang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.

关键词： Fuzzy adaptive Microgravity Robustness Space robot Trajectory tracking control

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Multi-objective power dispatch based on Q-learning algorithm considering reliability of ICPR

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Journal of Computational Information Systems 2015年第13期11卷 4665-4672页

作者： Wu, Zhongqiang Zhao, Liru Jia, Wenjing Wu, Changhan Wu, Lina Key Lab of Industrial Computer Control Engineering of Hebei Province College of Electric Engineering Yanshan University Qinhuangdao China

To solve the power dispatch problem with intermittent clear power resource (ICPR), the optimal power model which contains wind power, photovoltaic power, coal-fired power and variation load is built. The model allows the most utilization about ICPR, and minimizes the emission of coal-fired plants. On the hand of algorithm, Q-learning algorithm is used to solve this multi objectives power dispatch (MOPD) problem. The optimal solution is obtained by the fuzzy-based definition algorithm from the Pareto-front got by Q-learning algorithm. Simulation on IEEE30 system is curried out to illustrate the efficiency of proposed model and algorithm. ©, 2015, Journal of Computational Information Systems. All right reserved.

关键词： Wind power

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Cooperative Spectrum Sensing Based on Double Thresholds Energy Detection over Imperfect Reporting Channels

Cooperative Spectrum Sensing Based on Double Thresholds Ener...

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International Conference on Instrumentation, Measurement, computer, Communication and control (IMCCC)

作者： Zi Zhang Xinbin Li Zhixin Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei China

ISBN: (纸本)9781467377249

In this paper, the problem of hierarchical cooperative spectrum sensing using double thresholds energy detector over imperfect reporting channels will be investigated. When taking error effect on reporting decision into consideration, the sensing performance will be affected. In the proposed scheme, we analyze the performance of hierarchical cooperative spectrum sensing over imperfect reporting channels and the "majority-decision-aided" weighting rule will be used in the fusion center. The analysis and simulation results show that there is a significant performance loss when the decisions based on hierarchical spectrum sensing are transmitted over imperfect reporting channels and the sensing performance is improved by employing the new weighting rule.

关键词： Sensors Cognitive radio Signal to noise ratio computers Propagation losses Reliability Fading channels

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controlling velocity of armature based on the multi-pulse forming network

Controlling velocity of armature based on the multi-pulse fo...

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International Conference on Pulsed Power

作者： Zhenchun Wang Zhiyong Bao Fucai Liu Lijie Jia Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University QinHuangDao China

Given the accuracy of the muzzle velocity of railgun, based on the capacitive energy-stored type of pulse forming network, electromechanical model of railgun is established, a multistage multi-module velocity control strategy based on velocity closed-loop control is proposed. Through the simulate analyze of the multiple of PFU by using electromechanical model of railgun, the best PFU electrical parameters and the best multi-stage control strategy are obtained, test shows that the system model and the control strategy can be applied to the actual system experiment, and achieve good results.

关键词： Interference Load modeling Accuracy Velocity control Electromagnetics Capacitors

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Robust Iterative Learning control of Single-phase Grid-connected Inverter

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International Journal of Automation and computing 2014年第4期11卷 404-411页

作者： Zhong-Qiang Wu Chun-Hua Xu Yang Yang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

For the single phase inductance-capacitance-inductance(LCL) grid-connected inverter in micro-grid, a kind of robust iterative learning controller is designed. Based on the output power droop characteristics of inverter, the current sharing among the inverters is achieved. Iterative learning strategy is suitable for repeated tracking control and inhibiting periodic disturbance, and is designed using robust performance index, so that it has the ability to overcome the uncertainty of system parameters. Compared with the repetitive control, the robust iterative learning control can get high precision output waveform, and enhance the tracking ability for waveform, and the distortion problem of the output signal can be solved effectively.

关键词： Inductance-capacitance-inductance (LCL) filter iterative learning robust control power droop-characteristics repetitive control

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Hydraulic System Reliability Modelling and Analysis Based on Convex Model Bayesian Network

Hydraulic System Reliability Modelling and Analysis Based on...

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2015 International Conference on Fluid Power and Mechatronics

作者： Dongning Chen Yuliang Zhang Chengyu Yao Shijun Lv Key Lab of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

Compared with the probabilistic method, the nonprobabilistic convex model only requires a small number of samples and experiences to obtain the variation bounds of the ambiguous and imprecise parameters, and whereby makes the reliability analysis very convenient. In this paper, hydraulic lifting system reliability model is established and the reliability of the system is analyzed by convex model Bayesian network, then the reliability indices are described in the form of interval parameters. Using ellipsoid model to constrain interval model, the more accurate reliability indices are obtained. Finally the convex model Bayesian network is compared with traditional Bayesian network. All the reliability indices obtained by convex model Bayesian network provide the basis for condition-based maintenance, fault diagnosis and reliability design.

关键词： reliability analysis hydraulic system Bayesian network convex model

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Hydraulic System Reliability Modelling and Analysis Based on Convex Model Bayesian Network

Hydraulic System Reliability Modelling and Analysis Based on...

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International Conference of Fluid Power and Mechatronics

ISBN: (纸本)9781479987719

Compared with the probabilistic method, the non-probabilistic convex model only requires a small number of samples and experiences to obtain the variation bounds of the ambiguous and imprecise parameters, and whereby makes the reliability analysis very convenient. In this paper, hydraulic lifting system reliability model is established and the reliability of the system is analyzed by convex model Bayesian network, then the reliability indices are described in the form of interval parameters. Using ellipsoid model to constrain interval model, the more accurate reliability indices are obtained. Finally the convex model Bayesian network is compared with traditional Bayesian network. All the reliability indices obtained by convex model Bayesian network provide the basis for condition-based maintenance, fault diagnosis and reliability design.

关键词： Reliability analysis Hydraulic system Bayesian network Convex model

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Two-Stage Force Particle Swarm Optimization Algorithm and Application in Hydraulic System Reliability Optimization

Two-Stage Force Particle Swarm Optimization Algorithm and Ap...

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2015 International Conference on Fluid Power and Mechatronics

作者： Chengyu Yao Xueyun Tan Dongning Chen Shijun Lv Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Key Lab of Heavy Machinery Fluid Power Transmission and Control of Hebei Province Yanshan University

In view of the particle swarm optimization(PSO) algorithm's shortages of easily trapping into local optimum and premature convergence, an improvement research from the perspective of interaction mechanism among particles is made in this paper. Consider advantages and disadvantages of the current improved PSO algorithms from the aspect of force, the two-stage force particle swarm optimization(TFPSO) algorithm is proposed. The proposed algorithm, which employs staged search strategy to achieve a trade-off between global exploration and local exploitation abilities, divides search process into two stages and constructs corresponding force rules combining with the idea of attractive and repulsive forces in artificial physics. In order to demonstrate the performance of the proposed algorithm in solving optimization problems, TFPSO algorithm is compared with some well-known PSO algorithms in reliability optimization for hydraulic system. Comparison results show that TFPSO algorithm obtains the best optimization results and enhances the performance of PSO in terms of accuracy of the optimal solution and local search ability.

关键词： PSO algorithm force rule TFPSO algorithm reliability optimization hydraulic system

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Fuzzy PID control of Space Manipulator for Both Ground Alignment and Space Applications

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International Journal of Automation and computing 2014年第4期11卷 353-360页

作者： Fu-Cai Liu Li-Huan Liang Juan-Juan Gao Key Lab of Industrial Computer Control of Hebei Province Yanshan University

Considering gravity change from ground alignment to space applications, a fuzzy proportional-integral-differential(PID)control strategy is proposed to make the space manipulator track the desired trajectories in different gravity environments. The fuzzy PID controller is developed by combining the fuzzy approach with the PID control method, and the parameters of the PID controller can be adjusted on line based on the ability of the fuzzy controller. Simulations using the dynamic model of the space manipulator have shown the effectiveness of the algorithm in the trajectory tracking problem. Compared with the results of conventional PID control,the control performance of the fuzzy PID is more effective for manipulator trajectory control.

关键词： Space manipulator trajectory tracking ground alignment space applications fuzzy proportional-integral-differential (PID) gravity environment

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