Advanced Search
中文
Volume 43 Issue 6
Jun.  2021
Turn off MathJax
Article Contents
Abstract
References
Related Articles
CAI Yusheng, ZHU Jun, SHI Lei, ZHANG Jingzhong. Fuzzy Adaptive PID Control of Large Aperture Fast Steering Mirror[J]. Infrared Technology , 2021, 43(6): 523-531.
Citation: CAI Yusheng, ZHU Jun, SHI Lei, ZHANG Jingzhong. Fuzzy Adaptive PID Control of Large Aperture Fast Steering Mirror[J]. Infrared Technology , 2021, 43(6): 523-531.
shu

Fuzzy Adaptive PID Control of Large Aperture Fast Steering Mirror

  • 1.

    Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China

  • 3.

    Shandong Newclear Power Co. Ltd, Yantai 265116, China

  • 4.

    Heilongjiang Institute of Forest Protection, Harbin 150040, China

More Information
  • Received Date: December 23, 2020
  • Revised Date: December 29, 2020
    Graphical Abstract
    • Abstract
  • The ability of a fast-steering mirror (FSM) to track a target accurately and steadily depends on its servo control performance. The larger the aperture of the FSM is, the more difficult it is to design the flexible supporting hinge and the driver; in addition, it will also demand greater requirements on the servo control. To solve this problem, this paper proposes a fuzzy adaptive tune(FAT) proportional integral derivative (PID) control algorithm, which not only uses fuzzy theory for adaptively tuning the control parameters, but also inherits the classic PID controller for engineering realization. In this study, we designed a controller for the ϕ500 mm FSM driven by a voice coil motor, conducted simulation experiments, and compared the results with the simulation results based on classic PID control. According to the results, the overshoot was 5.4%, the settling time was 51.0 ms based on FAT PID control, and the capacity of resisting disturbance was stronger than that of the classical PID control. In addition, compared with traditional PID control, the proposed control method improved the ϕ500 mm FSM response speed, decreased the tracking error, and improved ϕ500 mm FSM system tracking performance and robustness.
    • FullText(HTML)
    • References (12)
  • [1]
    KLUK D J, BOULET M T, TRUMPER D L. A high-bandwidth, high-precision, two-axis steering mirror with moving iron actuator[J]. Mechatronics, 2012, 22(3): 257-270. DOI: 10.1016/j.mechatronics.2012.01.008
    [2]
    刘力双, 夏润秋, 吕勇, 等. 音圈电机快速控制反射镜研究现状[J]. 激光杂志, 2020, 9(1): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202009001.htm

    LIU Lishuang, XIA Runqiu, LV Yong, et al. Research situation of fast steering mirror driven by voice coil motor[J]. Laser Journal, 2020, 9(1): 1-7. https://www.cnki.com.cn/Article/CJFDTOTAL-JGZZ202009001.htm
    [3]
    艾志伟, 谭毅, 吴琼雁, 等. 改进根轨迹的快速反射镜控制参量设计[J]. 激光技术, 2017, 41(4): 558-561. https://www.cnki.com.cn/Article/CJFDTOTAL-JGJS201704020.htm

    AI Zhiwei, TAN Yi, WU Yanqiong, et al. Design of control parameters for fast steering mirrors by improving root locus[J]. Laser Technology, 2017, 41(4): 558-561. https://www.cnki.com.cn/Article/CJFDTOTAL-JGJS201704020.htm
    [4]
    魏文军, 赵雪童. 基于改进自抗扰的快速反射镜控制研究[J]. 红外技术, 2018, 40(11): 1071-1076. http://hwjs.nvir.cn/article/id/hwjs201811009

    WEI Wenjun, ZHAO Xuetong. Fast steering mirror control based on improved active disturbance rejection[J]. Infrared Technology, 2018, 40(11): 1071-1076. http://hwjs.nvir.cn/article/id/hwjs201811009
    [5]
    党选举. 压电陶瓷执行器的神经网络实时自适应逆控制[J]. 光学精密工程, 2008, 20(7): 1266-1272. DOI: 10.3321/j.issn:1004-924X.2008.07.020

    DANG Xuanju. Real-time adaptive inverse control based on neural networks for piezo ceramic actuator[J]. Optics and Precision Engineering, 2008, 20(7): 1266-1272. DOI: 10.3321/j.issn:1004-924X.2008.07.020
    [6]
    石磊, 许永森, 沈宏海, 等. 一种大口径偏摆镜[P]. 中国: CN 107526159B[2019-09-10].

    SHI Lei, XU Yongsen, SHEN Honghai, et al. A large-aperture deflection mirror[P]. CHINA : CN107526159B[2019-09-10].
    [7]
    欧长劲, 吴海列, 李军, 等. 基于模糊神经网络的SBR污水处理控制系统研究[J]. 计算机测量与控制, 2006, 14(12): 1643-1645. https://www.cnki.com.cn/Article/CJFDTOTAL-JZCK200612018.htm

    OU Changjin, WU Hailie, LI Jun, et al. Study of SBR control system based on fuzzy neural network[J]. Computer Measurement & Control, 2006, 14(12): 1643-1645. https://www.cnki.com.cn/Article/CJFDTOTAL-JZCK200612018.htm
    [8]
    陈泰潮. 基于模糊自适应PI控制的电梯调速系统仿真研究[J]. 机电技术, 2018, 3(1): 135-137. https://www.cnki.com.cn/Article/CJFDTOTAL-JDJS201303048.htm

    CHEN Taichao. Simulation research on elevator speed regulation system based on fuzzy adaptive PI control[J]. Mechanical & Electrical Technology, 2018: 3(1): 135-137. https://www.cnki.com.cn/Article/CJFDTOTAL-JDJS201303048.htm
    [9]
    赵继庭, 金刚石, 高旭辉. 基于快速反射镜的模糊自适应PID控制算法研究[J]. 激光与红外, 2018, 48(6): 756-761. DOI: 10.3969/j.issn.1001-5078.2018.06.016

    ZHAO Jiting, JIN Gangshi, GAO Xuhui. Fuzzy adaptive PID control algorithm based on fast steering mirror[J]. Laser & Infrared, 2018, 48(6): 756-761. DOI: 10.3969/j.issn.1001-5078.2018.06.016
    [10]
    Bullard A, Shawki I. Responder fast steering mirror[J]. Proceedings of SPIE - The International Society for Optical Engineering, 2013, 6(2): 88-91. DOI: 10.1117/12.2026443.full
    [11]
    于明星, 王瑛, 邵帅, 等. 基于Matlab的临界比例度法在工程PID参数自整定数值模拟中的应用[J]. 辽宁师专学报: 自然科学版, 2018, 2(1): 6-8. https://www.cnki.com.cn/Article/CJFDTOTAL-LAON201802002.htm

    YU Mingxing, WANG Ying, SHAO Shuai, et al. Application of critical proportioning method based on Matlab in PID parameters auto-tuning numerical simulation in engineering[J]. Journal of Liaoning Teachers College, 2018, 2(1): 6-8. https://www.cnki.com.cn/Article/CJFDTOTAL-LAON201802002.htm
    [12]
    孟子流, 李腾龙. 机器学习技术发展的综述与展望[J]. 集成电路应用, 2020, 37(10): 56-57. https://www.cnki.com.cn/Article/CJFDTOTAL-JCDL202010024.htm

    MENG Ziliu, LI Tenglong. Review and prospect of machine learning technology[J]. Application of IC, 2020, 37(10): 56-57. https://www.cnki.com.cn/Article/CJFDTOTAL-JCDL202010024.htm
    • Related Articles

  • Related Articles

    [1]XU Haiyang, ZHAO Wei, LIU Jianye. Infrared and Visible Image Registration Algorithm Based on Edge Structure Features[J]. Infrared Technology , 2023, 45(8): 858-862.
    [2]LI Bicao, LU Jiaxi, LIU Zhoufeng, LI Chunlei, ZHANG Jie. Infrared and Visible Light Image Fusion Method Based on Swin Transformer and Hybrid Feature Aggregation[J]. Infrared Technology , 2023, 45(7): 721-731.
    [3]WANG Xiangjun, DU Zhiwei, GAO Chao. Small Scale Fire Identification Based on Constrained Inhomogeneous Deformation Feature[J]. Infrared Technology , 2021, 43(2): 145-152.
    [4]LI Ruidong, SUN Xiechang, LI Meng. Infrared Feature Extraction and Recognition Technology of Space Target[J]. Infrared Technology , 2017, 39(5): 427-435.
    [5]ZHANG Chen, ZHAO Hong-ying, QIAN Xu. Research on Object Feature Tracking Method Oriented to UAV Images[J]. Infrared Technology , 2015, (3): 224-228,239.
    [6]ZHAO De-li, ZHU You-pan, WU Cheng, LI Ze-min, ZENG Bang-ze, LUO Lin, YANG Peng-wei, WANG Bing, LI Yan. Investigation on Improved Infrared Image Registration Algorithm Based on Point Feature and Gray Feature[J]. Infrared Technology , 2014, (10): 820-826.
    [7]Study on Image Registration Method Based on Region Feature[J]. Infrared Technology , 2010, 32(3): 145-147,151. DOI: 10.3969/j.issn.1001-8891.2010.03.006
    [8]CHEN Ya-bing, WANG Yong-zhong, WANG Yan-hua. IR Feature Extraction Based on Imbalance Fisher Discrimination[J]. Infrared Technology , 2008, 30(7): 395-398. DOI: 10.3969/j.issn.1001-8891.2008.07.007
    [9]LUO Xiao-an, CAI Chao, ZHOU Cheng-ping, DING Ming-yue, ZHANG Yi-guang, ZHANG Tian-xu. A New Fast Algorithm for Contour Descriptor[J]. Infrared Technology , 2006, 28(8): 446-452. DOI: 10.3969/j.issn.1001-8891.2006.08.004
    [10]ZHAO Qin, ZHOU Tao, SHU Qin. Discussion of Image Registration Based on Feature Points[J]. Infrared Technology , 2006, 28(6): 327-330. DOI: 10.3969/j.issn.1001-8891.2006.06.005

Catalog

    Get Citation
    PDF
    XML
    Article views PDF downloads Cited by()
    Related

    Copyright © 《Infrared Technology》Editorial Office滇ICP备12000354号-3

    Supported by: Beijing Renhe Information Technology Co., Ltd.  Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return