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第35届中国控制会议

作者： Zhang Xiuling Gao Wuyang Lai Yongjin Cheng Yantao Hou Daibiao Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan University

ISBN: (纸本)9781509009107

The present flatness pattern recognition method based on neural network belongs to software simulation,and it can't be directly applied to engineering ***'s more,the accuracy of present flatness pattern recognition is *** order to improve it,flatness pattern recognition via EA-ABC cloud inference network implemented by digital signal processor(DSP) is presented in this ***,based on T-S cloud inference network,flatness pattern recognition model is designed in *** it is applied to 900 HC reversible cold rolling ***,flatness pattern recognition model optimized by efficient adaptive artificial bee colony(EA-ABC) algorithm is ***,the two results of flatness pattern recognition model,which run onMATlab and DSP respectively,are compared and *** results confirm that EA- ABC algorithm has such advantages:high optimizing precision,less number of iterations,fast speed of *** pattern recognition model via EA-ABC cloud inference network can identify the defect types of flatness *** the same time,the experimental results verify that the T-S cloud inference network can run on the hardware TI TMS320F2812 in a fast speed and it provide a basis for neural network which is applied to practical engineering.

关键词： T-S cloud inference network flatness pattern recognition DSP hardware implementation EA-ABC algorithm

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An improved method for MRAC system of indirectly designed

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2012 International Conference on Cybernetics and Informatics, ICCI 2012

作者： Han, Huishan Liu, Yan Cheng, Defang Gao, Xue Xingtai Polytechnic College Xingtai 054000 China Key Lab. of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao 066004 China

ISBN: (纸本)9781461438717

Based on Lyapunov stability theorem, a MRAC system was researched to solve that differential value of plant output is unknown. Meanwhile an improved design for MRAC system aimed on the factor of restricting convergence of system is given. The method not only solves the problem that makes the system cannot work well as a result of the adjustable parameters, but also improves the convergence of plant. The simulation graphs have shown that the plant can follow the output of the reference model quit well © 2013 Springer Science+Business Media.

关键词： MRAC system Lyapunov theory Convergence model reference adaptive control Converge design improvement adjustable parameter Lyapunov methods plants

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A PD- Type iterative learning algorithm for networked control systems with missing data 2019

A PD- Type iterative learning algorithm for networked contro...

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2019 International Conference on Artificial Intelligence and computer Science, AICS 2019

作者： Cheng, Xiaoyan Dong, Yahui Wang, Hongbin Wang, Qinzhao Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China Weapon and Control Department Army Academy of Armored Forces Beijing100072 China

ISBN: (纸本)9781450371506

In this paper, a PD-type iterative learning control method is proposed for a class of nonlinear discrete networked control systems with measurement signal and control signal data dropouts. Proportional and differential items of the error signal are employed in this method to modify the current control signal, which takes full advantage of the historical error signals. The data dropout is described as a stochastic and independent Bernoulli process with a given probability. In addition, the zero-order holding method is introduced at the data receivers of the controller and actuator. Finally, the stability analysis and simulation results are performed to verify the convergence and effectiveness of the proposed method. © 2019 Association for Computing Machinery.

关键词： Networked control systems

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An Improved Hybrid Aquila Optimizer and Pigeon-Inspired Optimization Algorithm with Its Application in PID Parameter Optimization 8

An Improved Hybrid Aquila Optimizer and Pigeon-Inspired Opti...

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8th International Symposium on computer Science and Intelligent control, ISCSIC 2024

作者： Chen, Dongning Du, Xinwei Wang, Haowen Xian, Qinggui Sha, Jianhao Yao, Chengyu Yanshan University School of Mechanical Engineering Qinhuangdao China Yanshan University Hebei Key Laboratory of Industrial Computer Control Engineering Qinhuangdao China

ISBN: (纸本)9798350380286

To improve the optimization performance of the standard Aquila Optimizer (AO), an Improved Hybrid Aquila Optimizer and Pigeon-Inspired Optimization (IHAOPIO) algorithm based on stochastic balancing factor and Dimension-by-dimension Centroid Opposition-Based Learning (DCOBL) strategy is proposed. Wilcoxon test is introduced to statistically analyze the data of six classical benchmark functions. Compared with several other optimization algorithms, the proposed IHAOPIO algorithm has better optimization capability in accuracy. The improved algorithm is used to the PID parameter optimization of one electro-hydraulic position servo system and achieves good control effect. © 2024 IEEE.

关键词： Optimization algorithms

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A TCN-Transformer Model of Acceleration Prediction for Preceding Vehicle in CACC Systems 8

A TCN-Transformer Model of Acceleration Prediction for Prece...

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8th CAA International Conference on Vehicular control and Intelligence, CVCI 2024

作者： Tang, Wenzhao Tang, Wenbin Jiao, Xiaohong Zhang, Yahui Zhang, Dongxue Hebei Key Laboratory of Industrial Computer Control Engineering Yanshan University Hebei Province Qinhuangdao066004 China School of Mechanical Engineering Yanshan University Qinhuangdao066004 China

ISBN: (纸本)9798331504892

This study establishes an acceleration prediction model of the preceding vehicle tailored for cooperative adaptive cruise control (CACC) systems that address the common challenges posed by V2V communication delays or no communication from the preceding vehicle. The designed model integrates a temporal convolutional network (TCN) with the Transformer architecture block to create a sophisticated mechanism for temporal data analysis. This integration leverages the strengths of TCN in capturing spatial features and the multi-attention mechanism of Transformers to enhance the recognition of long-term dependencies in the time series of data. The synergy between these techniques not only effectively narrows the identification gap between short-term and long-term dependencies but also helps to process spatial information for accurate time-series prediction, significantly improving prediction accuracy. Simulations using the NGSIM dataset confirm the model's prediction performance over the traditional model. Further, the potential of the method to solve the communication delay problem is verified, highlighting the effectiveness of TCN and Transformer multi-attention mechanism in improving the CACC capability. © 2024 IEEE.

关键词： Adaptive cruise control

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A Measurement System for Railgun Test

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Defence Technology（防务技术） 2010年第2期6卷 150-154页

作者：王振春刘福才李惠光 Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University

A measurement system was designed to measure the railgun's parameters in launching process,which includes Rogowski coil sensor for measuring rail's current,B-dot probe for obversing projectile's velocity in bore,net target for catching muzzle velocity,signal condition circuit and high-speed data acquisition card for analyzing and storing *** software was also developed in WINDOWS operational environment via modularized *** designed sensors and test software were successfully used in a practical electromagnetic railgun system to monitor the process of *** test results indicate that the state of launching can be intuitively observed and the parameters are accurately acquired and *** software design method can shorten the development cycle,enhance the system's flexibility and provide the interface for the secondary *** system shows great *** is an effective and practical measurement platform for further research on the electromagnetic launch system.

关键词： electronics railgun measurement system Rogowski coil B-dot probe data acquisition

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Backstepping Sliding Mode control for Continuous Casting Mold Vibration Displacement System Driven by Servo Motor 36

Backstepping Sliding Mode Control for Continuous Casting Mol...

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第36届中国控制会议

作者： LI Jianxiong GUO Cui FANG Yiming ZHANG Qiyu Key Lab of Industrial Computer Control Engineering of Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

ISBN: (纸本)9781538629185

Aiming at the time-varying load torque disturbance in the vibration displacement system of continuous casting mold driven by servo motor,an extended state observer(ESO) based backsteppmg sliding mode control method is ***,a mapping function is established to deal with the non-uniqueness of the nonlinear inverse relationship from eccentric shaft angle to mold ***,an ESO is constructed to estimate the time-varying load torque,and the estimate of load torque is employed to compensate the disturbance in *** a backsteppmg sliding mode controller is then developed for the vibration displacement system of continuous casting mold,which can guarantee the asymptotical stability and the robust stability of the resulting closed-loop ***,simulation results are given to show the effectiveness of the proposed method.

关键词： servo motor drive system vibration displacement system extended state observer backstepping sliding mode control

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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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Improved Teaching-Learning-Based Optimization algorithms for function optimization 11

Improved Teaching-Learning-Based Optimization algorithms for...

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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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Open-closed Loop ILC Corrected with Angle Relationship of Output Vectors for Tracking control of Manipulator

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自动化学报 2010年第12期36卷 1758-1765页

作者： WANG Hong-Bin WANG Yan Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004P.R.China

In the research of iterative learning control (ILC), it is usually assumed that the initial states are consistent with the desired states or the initial states are fixed per iteration. By considering the problem that ILC law is difficult to apply to the tracking control for the manipulator under the restriction of initial states, we change the dynamic model of the manipulator system into a lower-order system by reduced-order transformations. For the transformed manipulator system, an open-closed loop ILC algorithm with angle correction term is proposed, which uses the error signal and the deviation of two adjacent error signals to adjust itself. Compared with traditional P-type algorithm, this algorithm makes better use of the saved and current information; while compared with PD-type algorithm, it overcomes the instability caused by the derivative action. Meanwhile, the angle relationship of output vectors is used as a standard to estimate the quality of the control inputs, “awarding or punishing” the changing trend of the algorithm. So, a fast convergence speed and excellent tracking effect are both realized. Improved strategies are proposed for the above algorithm when the limitation of each joint rotating angle is considered. Finally, the simulation results verify the effectiveness of the control scheme.

关键词： ILC 自动化跟踪控制仿真

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