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Fuzzy-PID controller for motion control of CFETR multi-functional maintenance platform

  • Li, Dongyi (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Lu, Kun (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Cheng, Yong (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Zhao, Wenlong (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Yang, Songzhu (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Zhang, Yu (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Li, Junwei (Institute of Plasma Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences) ;
  • Wu, Huapeng (Lappeenranta University of Technology)
  • Received : 2020.09.08
  • Accepted : 2021.01.25
  • Published : 2021.07.25

Abstract

The motion control of the divertor maintenance system of the China Fusion Engineering Test Reactor (CFETR) was studied in this paper, in which CFETR Multi-Functional Maintenance Platform (MFMP) was simplified as a parallel robot for the convenience of theoretical analysis. In order to design the motion controller of parallel robot, the kinematics analysis of parallel robot was carried out. After that, the dynamic modeling of the hydraulic system was built. As the large variation of heavy payload on MFMP and highly nonlinearity of the system, A Fuzzy-PID controller was built for self-tuning PID controller parameters by using Fuzzy system to achieve better performance. In order to test the feasibility of the Fuzzy-PID controller, the simulation model of the system was built in Simulink. The results have showed that Fuzzy-PID controller can significantly reduce the angular error of the moving platform and provide the stable motion for transferring the divertor.

Keywords

Acknowledgement

This work is supported by the National Key R&D Program of China with Grant No. 2017YFE0300503, Comprehensive Research Facility for Fusion Technology Program of China under Contract No. 2018000052-73-01-001228 and Anhui Extreme Environment Robot Engineering Laboratory. The authors would like to express their sincere gratitude to all the members of CFETR engineering design team.

References

  1. D. Li, K. Lu, Y. Cheng, W. Zhao, S. Yang, Y. Zhang, J. Li, S. Shi, Dynamic analysis of multi-functional maintenance platform based on Newton-Euler method and improved virtual work principle, Nuclear Engineering and Technology 52 (2020) 2630-2637. https://doi.org/10.1016/j.net.2020.04.017
  2. H.D. Taghirad, Parallel Robots: Mechanics and Control, first ed., CRC, Boca, Raton, 2013.
  3. S. Staicu, Dynamics of Parallel Robots, first ed., Springer, Cham, Switzerland, 2019.
  4. B. Siciliano, O. Khatib, Springer Handbook of Robotics, first ed., Springer, Heidelberg, Berlin, 2008.
  5. Wenliang Deng, Baomin Qiang, Simulation of Fuzzy-PID control of dual cylinder synchronous hydraulic system, Machine Tool & Hydraulics 38 (2010) 28-30.
  6. J. Anzurez, L.A. Torres, I.I. Lazaro, Fuzzy logic control for a two tanks hydraulic system model, in: IEEE Electronics, Robotics & Automotive Mechanics Conference, Cuernavaca, Mexico, November 15-18, 2011.
  7. Y. Jing, C. Xiaoming, Z. Yang, Y. Li, Cross-coupled fuzzy PID control combined with full decoupling compensation method for double cylinder servo control system, J. Mech. Sci. Technol. 32 (2018) 2261-2271. https://doi.org/10.1007/s12206-018-0437-9
  8. L. Zhixing, K. Xing, Application of fuzzy PID controller for electro-hydraulic servo position control system, in: 2017 3rd IEEE International Conference on Control Science and Systems Engineering, Beijing, China, August 17-19, 2017.
  9. S. Qian, L. Hak-Keung, X. Chengbin, M. Chen, Adaptive neuro-fuzzy PID controller based on twin delayed deep deterministic policy gradient algorithm, Neurocomputing 402 (2020) 183-194. https://doi.org/10.1016/j.neucom.2020.03.063
  10. J. Xin, C. Kaikang, Z. Yang, J. Jiangtao, P. Jing, Simulation of hydraulic transplanting robot control system based on fuzzy PID controller, Measurement 164 (2020) 108023. https://doi.org/10.1016/j.measurement.2020.108023
  11. B. Wafa, Y. AbuRmaileh, Decentralized motion control for omnidirectional wheelchair tracking error elimination using PD-fuzzy-P and GA-PID controllers, Sensors 20 (2020) 3525. https://doi.org/10.3390/s20123525
  12. C.B. Jabeur, H. Seddik, Design of a PID optimized neural networks and PD fuzzy logic controllers for a two-wheeled mobile robot, Asian J. Contr. 23 (1) (2020) 23-41.
  13. S. Bongsub, P. Jongwon, D. Yun, Depth-adaptive controller for spent nuclear fuel inspections, Nuclear Engineering and Technology 52 (2020) 1669-1676. https://doi.org/10.1016/j.net.2020.01.019
  14. S. Hocheol, J. Seung Ho, C. You Rack, C. Kim, Development of a shared remote control robot for aerial work in nuclear power plants, Nuclear Engineering and Technology 50 (2018) 613-618. https://doi.org/10.1016/j.net.2018.03.006
  15. K. Jong Seog, Y.H. Jang, Development of stable walking robot for accident condition monitoring on uneven floors in a nuclear power plant, Nuclear Engineering and Technology 49 (2017) 632-637. https://doi.org/10.1016/j.net.2016.10.004
  16. W. Sun, Hydraulic Control System, first ed., National defence industry press, Beijing, China, 1985.
  17. L. Zhang, Design and Use of Hydraulic Control System, first ed., Chemical Industry Press, Beijing, China, 2013.
  18. J. Lu, Automatic Control Theory, second ed., Northwestern Polytechnical University Press, Xi'an, China, 2009.
  19. Q. Liang, Q. Su, AMESim Computer Simulation Guide for Hydraulic System, first ed., China Machine Press, Bejing, China, 2014.
  20. X. Xu, Z.X. Li, H.L. Qin, Design and integrated simulation of the electrohydraulic servo system based on AMESim and matlab, Appl. Mech. Mater. 44-47 (2011) 1355-1359. https://doi.org/10.4028/www.scientific.net/AMM.44-47.1355
  21. Q. Guodong, J. Aihong, C. Yong, Z. Wenlong, P. Hongtao, S. Shanshuang, Y. Song, Design and analysis of the hydraulic driving system for the circular transfer platform of the CFETR divertor, Fusion Eng. Des. 156 (2020) 111598. https://doi.org/10.1016/j.fusengdes.2020.111598
  22. X.U. Bao-Qiang, W.U. Yong, Y. Wang, L.P. Zhan, Modeling and simulation of hydraulic cylinder position control based on AMESim, Coal Mine Machinery 36 (2015) 113-115.
  23. B. Wang, R.P. Xiong, Y.W. Zhao, Y. Deng, C.Y. Cheng, S.H. Shu, Research on pressure control of dual-pump direct-drive electro-hydraulic servo system based on AMESim-MATLAB joint simulation, Chin. Hydraul. Pneum. (2020) 171-176, 01.