FAST Node Displacement Control Method Using Self-Tunning Fuzzy PID Control

doi:10.12068/j.issn.1005-3026.2018.04.007

Journal of Northeastern University Natural Science ›› 2018, Vol. 39 ›› Issue (4): 487-491.DOI: 10.12068/j.issn.1005-3026.2018.04.007

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FAST Node Displacement Control Method Using Self-Tunning Fuzzy PID Control

SHA Yi¹， FAN Qian-wen¹， ZHANG Li-li¹， ZHU Li-chun²

1. School of Computer Science & Engineering， Northeastern University， Shenyang 110169， China; 2. National Astronomical Observatories， Chinese Academy of Sciences， Beijing 100012， China.

Received:2016-11-22 Revised:2016-11-22 Online:2018-04-15 Published:2018-04-10
Contact: SHA Yi
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Abstract

Abstract: To solve the problem of achieving the expected moving position of more than 2400 nodes under the influence of the tension of adjacent points， wind， temperature and other factors， FAST node displacement control method was studied by using the self-tuning fuzzy PID combined with the improved scheme of variable domain scaling. By analyzing FAST node hydraulic actuator servo system， a transfer function of the controlled object was obtained. The controller was designed by analyzing the error and its corresponding rate of change， and feasible and effective variable domain scaling factor was chosen. The improved algorithm was modeled and simulated by Simulink. The results showed the feasibility of self-tuning PID control based on the variable domain for the FAST node displacement control.

Key words: FAST node displacement, self-tuning PID control, fuzzy control, variable domain

CLC Number:

TP393.17

SHA Yi， FAN Qian-wen， ZHANG Li-li， ZHU Li-chun. FAST Node Displacement Control Method Using Self-Tunning Fuzzy PID Control[J]. Journal of Northeastern University Natural Science, 2018, 39(4): 487-491.

References

[1]南仁东.500m球反射面射电望远镜FAST［J］.中国科学，2005，35(5):449-466.(Nan Ren-dong.500m ball reflector radio telescope［J］.Chinese Science，2005，35(5):449-466.)
[2]Hajebi P.Online adaptive fuzzy logic controller using genetic algorithm and neural network for networked control systems［C］// 15th International Conference on Advanced Communications Technology.Gangwon，2013:88-98.
[3]Liu X D.The development of fuzzy rough sets with the use of structures and algebras of axiomatic fuzzy sets［J］.IEEE Transactions on Knowledge and Data Engineering，2009，21(3):443-462.
[4]蔡文皓，李齐齐，李都.模糊 PID 算法在光伏电池 MPPT 中的仿真研究［J］.电源技术，2016，140(4):786-788.(Cai Wen-hao，Li Qi-qi，Li Du.Simulation study of photovoltaic cells MPPT using fuzzy self-tuning PID algorithm［J］.Power Technology，2016，140(4):786-788.)
[5]王天田.FAST工程主动反射面液压促动器的研究［D］.秦皇岛:燕山大学，2015:38-50.(Wang Tian-tian.Research on hydraulic actuator of FAST active reflector system［D］.Qinhuangdao:Yanshan University，2015:38-50.)
[6]Zhang F，Lu Y H，Qiao F.Self-tuning fuzzy adaptive PID pitch control of wind power systems［C］//Proceedings of International Conference on Mechatronics，Applied Mechanics and Energy Engineering.Hangzhou，2013:404-409.
[7]Chebli S，Elakkary A.PID controller tuning using multi-objective ant colony optimization applied to TCP/AQM networks［C］// 23rd International Conference on Automation and Computing.London，2017:1-6.
[8]Ibidapo-Obe O.On development of fuzzy controller:the case of Gaussian and triangular membership functions［J］.Journal of Signal and Information Processing， 2011，2(4):257-265.
[9]郭海刚，李洪兴，胡凯.一类变论域自适应模糊控制器［J］.模糊系统与数学，2011，25(6):1-9.(Guo Hai-gang，Li Hong-xing，Hu Kai.A novel variable universe adaptive fuzzy controller［J］.Fuzzy Systems and Mathematics，2011，25(6):1-9.)
[10]朱丽春.FAST主反射面自动控制系统［J］.科学技术与工程，2006，6(13):1890-1891.(Zhu Li-chun.The arithmetic control system of active reflector for FAST［J］.Science Technology and Engineering，2006，6(13):1890-1891.)

FAST Node Displacement Control Method Using Self-Tunning Fuzzy PID Control

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