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Optimal Control Method of Motor Torque Loading Based on Genetic Algorithm

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Intelligent Robotics and Applications (ICIRA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13455))

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Abstract

This paper designs an automatic calibration method and system of motor torque for the problem of low loading accuracy of motor torque. The system uses genetic algorithm to optimize PID parameters and load control and measurement of the motor. The genetic algorithm is realized in the simulation platform, and the iterative operation is carried out by setting different cross probability and mutation probability parameters. The results are substituted into the motor model to analyze the response speed and anti-interference ability of the motor to the given random signal, and the optimal PID parameters are obtained as the configuration parameters of the motor torque automatic calibration system. The experimental results show that compared with the traditional motor torque calibration loading control, the accuracy of the system torque calibration error is improved and the error range is controlled within ±0.003 N \(\cdot \) m, which verifies the effectiveness and feasibility of this method.

This work was supported by the National Key R &D Program of China under Grant No. 2018AAA0101000.

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Authors and Affiliations

  1. Beijing Institute of Technology, Beijing, 100081, China

    Shaohua Niu, Wencai Zhang, Tianzhen Li & Gan Zhan

Authors
  1. Shaohua Niu
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  2. Wencai Zhang
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  3. Tianzhen Li
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  4. Gan Zhan
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Corresponding author

Correspondence to Gan Zhan .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Shenzhen, China

    Honghai Liu

  2. Huazhong University of Science and Technology, Wuhan, China

    Zhouping Yin

  3. Shenyang Institute of Automation, Shenyang, Liaoning, China

    Lianqing Liu

  4. Harbin Institute of Technology, Harbin, China

    Li Jiang

  5. Shanghai Jiao Tong University, Shanghai, China

    Guoying Gu

  6. Shenzhen Institute of Advanced Technology, Shenzhen, China

    Xinyu Wu

  7. Harbin Institute of Technology, Shenzhen, China

    Weihong Ren

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Niu, S., Zhang, W., Li, T., Zhan, G. (2022). Optimal Control Method of Motor Torque Loading Based on Genetic Algorithm. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13455. Springer, Cham. https://doi.org/10.1007/978-3-031-13844-7_21

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  • DOI: https://doi.org/10.1007/978-3-031-13844-7_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13843-0

  • Online ISBN: 978-3-031-13844-7

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