Research on Fuzzy-PID Control for Contra Rotating PMBLDCM

Abstract:

The system of contra rotating PMBLDCM widely used in underwater vehicle is a non-linear, multi-variable, time-varying system. Using the traditional method for PID control is difficult to achieve fine control effect. By designing a Fuzzy-PID controller, fuzzy algorithm for on-line auto-tuning PID parameters is applied to the system of a speed closed-loop in PMBLDCM double closed-loop system. An example of how to design and simulate the system by using the software MATLAB is introduced. The simulation results show that the method of Fuzzy-PID control has better control performance comparing with the conventional PID control, it has characteristics of no overshoot, fast response, small torque ripple.

• Periodical: Advanced Materials Research (Volume 505)
• Pages: 227-232
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.505.227
• Online since: April 2012
• Authors: Yan Sheng Li, Man Feng Dou, Jin Li Lei
• Keywords: BLDCM, Contra-Rotating, Fuzy Control, PID

References

[1] Xiu-hua Shi, Xiaojuan Wang. Introduction to underwater weapons (torpedo volumes) [M]. Xi'an: Northwest Industry University Press, (2005)

[2] LIW. Design of a hybrid fuzzy logic proportional plus conventional integral-derivative controller[J]. IEEE Trans on Fuzzy Systems, 1998, 4 (6) ,pp.449-463.

DOI: 10.1109/91.728430

[3] H Kenichiro, et a.l Realization of nonlinear PID controls using simp lified indirect fuzzy inference method[J]. Elesevier Science on Fuzzy Sets and Systems, 1999, 105,pp.409-414.

DOI: 10.1016/s0165-0114(97)00248-0

[4] Heidar A M Davem, C Guanrong. Design and analysis of a fuzzy proportional integral derivative controller[J].Elsevier Science on Fuzzy Sets and Systems, 1996, 79,pp.297-314.

DOI: 10.1016/0165-0114(95)00149-2

[5] Qin Chang, Jianqi Qiu so. Double Rotating Permanent Magnet Brushless DC Motor Modeling and Simulation [J]. CSEE, 2004,12(4)

[6] Zhicheng Ji, Yanxia Shen, Hua Xue. Study on the adaptive fuzzy control for brushless DC motor[J].Zhongguo Dianji Gongcheng Xuebao, 2005, 25(5) , pp.104-109

[7] Mianhua Wang. The fuzzy-PI control of switched relunctance motor based on DTC[C]. 2009 International Conference on Measuring Technology and Mechatronics Automation,2009, pp.606-609

DOI: 10.1109/icmtma.2009.533

[8] Huiping Wang, Yentan Liu. Integrated design of speed-sensorless and adaptive speed controller for a brushless dc motor[J].IEEE Transactions on Power Electronics, 2006, 21(2), pp.518-523

DOI: 10.1109/tpel.2005.869772

[9] Jianxin Yang, Yonggui Du. Self-adaptive Tuning of Fuzzy PID Controller and Its Simulation[J].Mechanical Engineering & Automation,2006.10(5),pp.110-112.

[10] Changliang Xia, Zhiqiang Li. Single Neuron PID Model Reference Adaptive Control for PM Rushless DC Motors Based on RBF Neural Network On-Line Identification[J].Transactions of China Electrotechnical Society,2005,20(11),pp.66-68

DOI: 10.1109/icca.2007.4376429

[11] Haibo Jiang, Xinyi Cui, Lingbo Zeng, Huijun Zhou. Modeling and simulation of brushless DC motor fuzzy control system[J]. Journal of Xi'an Jiaotong University, 2005, 39(10), pp.1116-1120

[12] Yongan Huang, Lu Ma. MATLAB7.0/Simulink6.0 modeling and simulation development and advanced engineering applications [M]. Beijing: Tsinghua University Press, 2005.