The Speed Control of Brushless DC Motor Based on Fuzzy Genetic Algorithm

被引:0
作者
Gu Deying [1 ]
Xia Rui [1 ,2 ]
机构
[1] Northeastern Univ Qinhuangdao, Dept Automat Engn, Qinhuangdao 066004, Peoples R China
[2] Northeastern Univ, Sch Informat Sci & Engn, Shenyang 110000, Peoples R China
来源
2013 25TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2013年
关键词
BLDCM; Fuzzy control; Genetic Algorithm; MATLAB;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, the speed control of brushless DC motor based on fuzzy Genetic Algorithm is discussed. The paper uses Genetic Algorithm to optimize the control rules, membership function and scaling factors of fuzzy control system. At last, the simulation of optimized fuzzy control system is carried out. The result of simulation indicated that the optimized control system could give a good control performance.
引用
收藏
页码:3737 / 3740
页数:4
相关论文
共 7 条
  • [1] Automatic generation of fuzzy rule-based models from data by genetic algorithms
    Angelov, PP
    Buswell, RA
    [J]. INFORMATION SCIENCES, 2003, 150 (1-2) : 17 - 31
  • [2] Determination of fuzzy logic membership functions using genetic algorithms
    Arslan, A
    Kaya, M
    [J]. FUZZY SETS AND SYSTEMS, 2001, 118 (02) : 297 - 306
  • [3] Determination of scaling factors for fuzzy logic control using the sliding-mode approach: Application to control of a DC machine drive
    Betin, Franck
    Sivert, Arnaud
    Yazidi, Amine
    Capolino, Gerard-Andre
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2007, 54 (01) : 296 - 309
  • [4] GA-based fuzzy controller design for tunnel ventilation systems
    Chu, Baeksuk
    Kima, Dongnam
    Hong, Daehie
    Park, Jooyoung
    Chungb, Jin Taek
    Chung, Jae-Hun
    Kim, Tae-Hyung
    [J]. AUTOMATION IN CONSTRUCTION, 2008, 17 (02) : 130 - 136
  • [5] Adaptive crossover, mutation and selection using fuzzy system for genetic algorithms
    Im, Soung-Min
    Lee, Ju-Jang
    [J]. ARTIFICIAL LIFE AND ROBOTICS, 2008, 13 (01) : 129 - 133
  • [6] A fuzzy genetic algorithm for the discovery of process parameter settings using knowledge representation
    Lau, H. C. W.
    Tang, C. X. H.
    Ho, G. T. S.
    Chan, T. M.
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (04) : 7964 - 7974
  • [7] Experimental verification of a hybrid fuzzy control strategy for a high-performance brushless DC drive system
    Rubaai, A
    Ricketts, D
    Kankam, MD
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2001, 37 (02) : 503 - 512