Volume 13 Issue 6
Dec.  2020
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Chinese Optics  > 2020  >  13(6): 1314-1323.
DONG Quan-rui, CHEN Tao, GAO Shi-jie, LIU Yong-kai, ZHANG Jian-qiang, WU Hao. Identification of opto-electronic fine tracking systems based on an improved differential evolution algorithm[J]. Chinese Optics, 2020, 13(6): 1314-1323. doi: 10.37188/CO.2020-0021
Citation: DONG Quan-rui, CHEN Tao, GAO Shi-jie, LIU Yong-kai, ZHANG Jian-qiang, WU Hao. Identification of opto-electronic fine tracking systems based on an improved differential evolution algorithm[J]. Chinese Optics, 2020, 13(6): 1314-1323. doi: 10.37188/CO.2020-0021
shu

Identification of opto-electronic fine tracking systems based on an improved differential evolution algorithm

  • 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

Funds:  Supported by National Key R & D Program of China (No. 2016YFB0500100); Fudan University-CIOMP Joint Fund (No. Y8O732E); Civil Aerospace Pre-research Project (No. D04010)
More Information
  • Corresponding author: chent@ciomp.ac.cn
  • Received Date: 11 Feb 2020
  • Rev Recd Date: 25 Mar 2020
    • Available Online: 15 Oct 2020
  • Publish Date: 01 Dec 2020
    Abstract
  • In this paper, an identification method based on an improved differential evolution algorithm is proposed for laser communication fine tracking systems. Firstly, the basic principle and calculation steps of the traditional differential evolution algorithm are introduced. Based on this, an improved algorithm is proposed, and the algorithm’s parameters are optimized . Then, the dynamic characteristics of a controlled object in the fine tracking system are simulated by a sweep signal, and the positional feed back information of the camera is collected. Finally, based on the experimental data, the differential evolution algorithm is used to identify the system, and the control model of the fine tracking system is obtained. The experimental results show that the improved differential evolution algorithm has faster convergence speed and accurate identification results. In general, this method has engineering value in the field of optoelectronic tracking.

     

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