Research on improved active disturbance rejection control of continuous rotary motor electro-hydraulic servo system

连续回转马达电液位置伺服系统的改进自抗扰控制

Abstract

In order to meet the precision requirements and tracking performance of the continuous rotary motor electro-hydraulic servo system under unknown strong non-linear and uncertain strong disturbance factors, such as dynamic uncertainty and parameter perturbation, an improved active disturbance rejection control (ADRC) strategy was proposed. The state space model of the fifth order closed-loop system was established based on the principle of valve-controlled hydraulic motor. Then the three parts of ADRC were improved by parameter perturbation and external disturbance; the fast tracking differentiator was introduced into linear and non-linear combinations; the nonlinear state error feedback was proposed using synovial control; the extended state observer was determined by nonlinear compensation. In addition, the grey wolf algorithm was used to set the parameters of the three parts. The simulation and experimental results show that the improved ADRC can realize the system frequency 12 Hz when the tracking accuracy and response speed meet the requirements of double ten indexes, which lay foundation for the motor application.

摘要

为满足连续回转电液伺服马达系统在动态不确定性、 参数摄动等未知强非线性和不确定强扰动因素下的精度需求和跟踪性能, 提出了一种改进自抗扰控制(ADRC)策略. 在阀控液压马达原理的基础上, 建立马达五阶闭环系统状态空间模型. 利用参数摄动和外部扰动对自抗扰控制器三部分进行改进, 引入线性与非线性组合的快速跟踪微分器, 提出用滑膜控制改进非线性状态误差反馈控制律, 确定非线性补偿的扩张状态观测器. 利用灰狼算法分别对三个部分进行参数整定. 结果表明, 在跟踪精度和响应速度均满足双十指标要求下, 改进自抗扰控制器能够使系统频率达到 12 Hz, 为马达的实际应用奠定了基础.

This is a preview of subscription content, access via your institution.

References

  1. [1]

    WANG Xiao-jing, LIU Mei-zhen, CHEN Shuai, LI Song. Predictive function and sliding model controller of continuous rotary electro-hydraulic servo motor applied to simulator [J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(5): 1547–1557. DOI: https://doi.org/10.13229/j.cnki.jdxbgxb20180507. (in Chinese)

    Google Scholar 

  2. [2]

    YUAN Li-peng, CUI Shu-mei, LU Hong-ying, LI Shang-yi. Research on low speed performance of electro-hydraulic servomotor based on improved simulated annealing genetic algorithm [J]. Journal of Shanghai Jiao Tong University, 2010, 44(12): 1741–1746. DOI: https://doi.org/10.16183/j.cnki.jsjtu.2010.12.022. (in Chinese)

    Google Scholar 

  3. [3]

    CAO Jian, MA Yu-hua, WU Xiao-feng. Application of QFT in continuous rotary electro-hydraulic servo motor [J]. Journal of Harbin Institute of Technology, 2009, 41(11): 69–72, 128. DOI: CNKI:SUN:HEBX.0.2009-11-014. (in Chinese)

    Google Scholar 

  4. [4]

    YUAN Li-peng. Structure optimization for improving low speed performance of continuous rotary electro-hydraulic servomotor based on the improved genetic algorithm [J]. Journal of Mechanical Engineering, 2010, 46(12): 166–174. DOI: CNKI:SUN:JXXB.0.2010-12-029.

    Article  Google Scholar 

  5. [5]

    LI Min-zhao. Simulation Analysis of Disturbance suppression by ADRC [J]. Scientific and Technological Innovation, 2019(23): 47–48.

    Google Scholar 

  6. [6]

    LI Min-zhao. Simulation analysis of active disturbance rejection control technology based on simulink [J]. China Computer & Communication, 2019(1): 167–168, 171. DOI: CNKI:SUN:XXDL.0.2019-01-075. (in Chinese)

    Google Scholar 

  7. [7]

    ZHAO Zhi-liang. Active disturbance rejection control technology and theoretical analysis [M]. Beijing: Science Press, 2019.

    Google Scholar 

  8. [8]

    MA Zhuang, LIU Peng, WANG Jian-long. Simulation study on classical RLC system based on active disturbance rejection control [J]. Journal of Tangshan University, 2019, 32(6): 5–8, 42. DOI: https://doi.org/10.16160/j.cnki.tsxyxb.2019.06.002. (in Chinese)

    Google Scholar 

  9. [9]

    TIAN Gang, GAO Zhi-qiang. Frequency response analysis of active disturbance rejection based control system [C]// Proceedings of the 16th IEEE International Conference on Control, Applications Part of IEEE Multi-conference on Systems and Control. Singapore: IEEE, 2007: 1595–1599. DOI: https://doi.org/10.1109/CCA.2007.4389465.

    Google Scholar 

  10. [10]

    XIA Yuan-qing, FU Meng-yin, DENG Zhi-hong, REN Xuemei. Recent developments in sliding mode control and active disturbance rejection control [J]. Control Theory & Applications, 2013, 30(2): 137–147. DOI: https://doi.org/10.7641/CTA.2013.20498. (in Chinese)

    MATH  Google Scholar 

  11. [11]

    SHEN Wei, CUI Xia. Study on hydraulic motor speed servo system controlled by proportional servo valves with active disturbance rejection controller [J]. Computer Simulation, 2016, 33(8): 317–321. DOI: https://doi.org/10.3969/j.issn.1006-9348.2016.08.069. (in Chinese)

    Google Scholar 

  12. [12]

    MA Shun-jian, SUN Ming-wei, CHEN Zeng-qiang. Interactive ADRC design for flight attitude control [C]// Proceedings of 2017 IEEE 6th Data Driven Control and Learning Systems Conference(DDCLS’17). IEEE Beijing Section. Beijing: IEEE Industrial Electronics Society, 2017. DOI: https://doi.org/10.1109/ddcls.2017.8068142.

    Google Scholar 

  13. [13]

    ZHANG Xi-dan, YIN Da-yi. Simulation study of active disturbance rejection controller for high order systems [J]. Aerospace Control, 2018, 36(1): 3–7, 13. DOI: https://doi.org/10.16804/j.cnki.issn1006-3242.2018.01.001. (in Chinese)

    Google Scholar 

  14. [14]

    CHEN Zeng-qiang, LIU Jun-jie, SUN Ming-wei. Overview of a novel control method: active disturbance rejection control technology and its practical applications [J]. CAAI Transactions on Intelligent Systems, 2018, 13(6): 865–877. DOI: https://doi.org/10.11992/tis.201711029. (in Chinese)

    Google Scholar 

  15. [15]

    FU Cai-fen, TAN Wen. Parameters tuning of linear active disturbance rejection control based on high order controller design [J]. Control Theory & Applications, 2017, 34(2): 265–272. DOI: https://doi.org/10.7641/CTA.2017.60039. (in Chinese)

    MathSciNet  MATH  Google Scholar 

  16. [16]

    GUO Bao-zhu, ZHAO Zhi-liang. Active disturbance rejection control: Theoretical perspectives [J]. Communications in Information and Systems, 2015, 15(3): 361–421. DOI: https://doi.org/10.4310/CIS.2015.v15.n3.a3.

    MathSciNet  Article  Google Scholar 

  17. [17]

    ZHANG Hua, ZHENG Jia-qiang. Study on the design method of an active disturbance rejection optimal controller [J]. Control Engineering, 2018, 25(12): 2219–2223. DOI: https://doi.org/10.14107/j.cnki.kzgc.161003.

    Google Scholar 

  18. [18]

    ZHANG Meng, YU Jian, PANG Qing-wen, ZHAO Mo-lin. Research on auto disturbance rejection parameter tuning based on multi target moth optimization algorithm [J]. Microelectronics & Computer, 2018, 35(11): 84–88. DOI: CNKI:SUN:WXYJ.0.2018-11-017. (in Chinese)

    Google Scholar 

  19. [19]

    LIU Chun-fang, ZANG Bin. Application and the parameter tuning of ADRC based on CPSO [C]// Proceedings of the 24th Chinese Control and Decision Conference. Taiyuan: IEEE, 2012: 3277–3281. DOI: https://doi.org/10.1109/CCDC.2012.6243084.

    Google Scholar 

  20. [20]

    HU Yi, WANG Min-gang, YANG Yao. Parameters tuning of active disturbance rejection controller (ADRC) based on artificial fish swarm algorithm (AFSA) [J]. Command Control & Simulation, 2013, 35(2): 90–92, 107. (in Chinese)

    Google Scholar 

  21. [21]

    LI Jia-hao, SUN Hong-fei. Improvement and application of active disturbance rejection control [J]. Journal of Xiamen University (Natural Science Edition), 2018, 57(5): 695–701. DOI: CNKI:SUN:XDZK.0.2018-05-017. (in Chinese)

    MathSciNet  MATH  Google Scholar 

  22. [22]

    SUN Yu-meng, ZHANG Xu-xiu. Parameter setting and application of ADRC by improved genetic algorithm [J]. Automation and Instrumentation, 2020, 35(3): 13–17, 45. DOI: https://doi.org/10.19557/j.cnki.1001-9944.2020.03.004.

    Google Scholar 

  23. [23]

    HAN Wen-jie, TAN Wen. Parameter tuning of linear ADRC based on PID parameter tuning [EB/OL]. [2020-06-16]. https://doi.org/10.13195/j.kzyjc.2019.1408.

  24. [24]

    ZHOU Tao. Parameter optimization of linear ADRC based on differential evolution algorithm [EB/OL]. [2020-06-16]. http://kns.cnki.net/kcms/detail/41.1228.TJ.20200219.0959.002.html.

  25. [25]

    BAI Jie, ZHU Ri-xing, WANG Wei, MA Zhen. Control method based on linear ADRC controller design [J]. Science, Technology and Engineering, 2020, 20(10): 4149–4153.

    Google Scholar 

  26. [26]

    GAO Yang, WU Wen-hai, GAO Li. Linear ADRC for high order uncertain nonlinear systems [J]. Control and Decision, 2020, 35(2): 483–491. DOI:https://doi.org/10.13195/j.kzyjc.2018.0550.

    Google Scholar 

  27. [27]

    LIU Jun-feng, YANG Zhe, LI Ding-fang. A multiple search strategies based grey wolf optimizer for solving multi-objective optimization problems [J]. Expert Systems with Applications, 2020, 145: 113134. DOI: https://doi.org/10.1016/j.eswa.2019.113134.

    Article  Google Scholar 

  28. [28]

    RASHID T A, ABBAS D K, TUREL Y K. A multi hidden recurrent neural network with a modified grey wolf optimizer [J]. PloS One, 2019, 14(3). DOI: https://doi.org/10.1371/journal.pone.0213237.

    Google Scholar 

  29. [29]

    ZHANG Hua, ZHENG Jia-qiang, XU You-lin. Study of auto disturbance rejection synchronous control for bilateral hydraulic motor of concept sprayer chassis [J]. Journal of China Agricultural University, 2017, 22(6): 135–143. DOI: https://doi.org/10.11841/j.issn.1007-4333.2017.06.16. (in Chinese)

    Google Scholar 

  30. [30]

    YANG Guo-lai, WANG Hao-ze, GUO Long, HUANG Su-dan, GONG Wen-na. Simulation research on dynamic characteristic control of hydraulic valve-controlled motor [J]. Hydraulics Pneumatics & Seals, 2017, 37(1): 27–30. DOI: https://doi.org/10.3969/j.issn.1008-0813.2017.01.006. (in Chinese)

    Google Scholar 

  31. [31]

    HE Han-lin. Research on frequency domain and time domain dynamic characteristics of servo valve [J]. Hydraulics Pneumatics & Seals, 2019, 39(11): 26–28, 32.

    Google Scholar 

  32. [32]

    SHENG Xi-zheng, ZHONG Xiao-qin, XU Yi, JI Qi-qiang. Design and simulation analysis of electro-hydraulic position servo system [J]. Laboratory Research and Exploration, 2019, 38(4): 85–89. DOI: CNKI:SUN:SYSY.0.2019-04-022.

    Google Scholar 

  33. [33]

    YAO Zhi-ying, CAO Hai-qing. A novel tracking differentiator with good stability and rapidity and its application [J]. Transactions of Beijing Institute of Technology, 2018, 38(8): 861–867. DOI: CNKI:SUN:BJLG.0.2018-08-015. (in Chinese)

    MathSciNet  Google Scholar 

  34. [34]

    LIU Zhi-gao. Design of improved tracking differentiator [J]. Navigation and Control, 2018, 17(4): 61–65. DOI: CNKI:SUN:DHKZ.0.2018-04-011.

    Google Scholar 

  35. [35]

    CHE Jian-feng. Research on control of four rotor UAV Based on sliding mode auto disturbance rejection technology [D]. Tianjin: Tianjin University of Technology, 2019. (in Chinese)

    Google Scholar 

  36. [36]

    CHEN De-min, GU Hong-yan, ZHANG Dong-dong, AN Yin-min. Active disturbance rejection control for steam temperature system of circulating fluidized bed boiler [J]. Journal of Guizhou University, 2019, 36(3): 91–95. DOI: https://doi.org/10.15958/j.cnki.gdxbzrb.2019.03.17. (in Chinese)

    Google Scholar 

  37. [37]

    ZHOU Zhi-gang. Application of active disturbance rejection control in superheated steam temperature and parameter optimization [D]. North China Electric Power University, 2019. (in Chinese)

    Google Scholar 

  38. [38]

    MIRJALILI S, MIRJALILI S M, LEWIS A. Grey wolf optimizer [J]. Advances in Engineering Software, 2014, 69: 46–61. DOI: https://doi.org/10.1016/j.advengsoft.2013.12.007.

    Article  Google Scholar 

  39. [39]

    ESWARAMOORTHY S, SIVAKUMARAN N, SEKARAN S. Grey wolf optimization based parameter selection for support vector machines [J]. COMPEL-the International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 2016, 35(5): 1513–1523. DOI: https://doi.org/10.1108/COMPEL-09-2015-0337.

    Article  Google Scholar 

  40. [40]

    JITKONGCHUEN D, PHAIDANG P, PONGTAWEVIRAT P, PIYALAK P. An adaptive elitism-based immigration for grey wolf optimization algorithm [C]// 2017 International Conference on Digital Arts, Media and Technology (ICDAMT). IEEE, 2017. DOI: https://doi.org/10.1109/ICDAMT.2017.7904965.

    Google Scholar 

Download references

Author information

Affiliations

Authors

Contributions

The overarching research goals were developed by WANG Xiao-jing, FENG Ya-ming, and SUN Yu-wei. WANG Xiao-jing established the mathematical model of the valve controlled motor, compiled the experimental program, calculated and analyzed the measured data. FENG Ya-ming and SUN Yu-wei designed the improved ADRC and adjusted the parameters to get the simulation curve. The initial draft of the manuscript was written by WANG Xiao-jing, FENG Ya-ming and SUN Yu-wei. All authors replied to reviewers’ comments and revised the final version.

Corresponding author

Correspondence to Xiao-jing Wang 王晓晶.

Ethics declarations

WANG Xiao-jing, FENG Ya-ming and SUN Yu-wei declare that they have no conflict of interest.

Additional information

Foundation item: Project(51975164) supported by the National Natural Science Foundation of China; Project(2019-KYYWF-0205) supported by the Fundamental Research Foundation for Universities of Heilongjiang Province, China

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Wang, Xj., Feng, Ym. & Sun, Yw. Research on improved active disturbance rejection control of continuous rotary motor electro-hydraulic servo system. J. Cent. South Univ. 27, 3733–3743 (2020). https://doi.org/10.1007/s11771-020-4573-x

Download citation

Key words

  • continuous rotary electro-hydraulic servo motor
  • active disturbance rejection control (ADRC)
  • fast tracking differentiator (TD)
  • non-linear state error feedback (NLSEF)
  • extended state observer (ESO)
  • grey wolf algorithm

关键词

  • 连续回转电液伺服马达
  • 自抗扰控制
  • 快速跟踪微分器
  • 非线性状态误差反馈控制律
  • 扩张状态观测器
  • 灰狼算法