AI熱潮下無刷直流電機模糊智能控制算法研究綜述
徐敬成1,2,凌云1,2,侯文浩1,2
(1 湖南工業(yè)大學 電氣與信息工程學院,湖南 株洲 412007;2 電傳動控制與智能裝備湖南省重點實驗室,湖南 株洲 412007)
摘 要:在人工智能(AI)研究領域,智能控制的實現(xiàn)方法各不相同。分別對人工智能、無刷直流電機調速系統(tǒng)和模糊控制進行具體闡述,并分析了模糊控制在無刷直流電機模糊智能調速系統(tǒng)中的研究現(xiàn)狀與發(fā)展前景,指出由于模糊系統(tǒng)的參數(shù)和規(guī)則靠經驗來選擇難免會存在缺陷,只有結合不同算法的優(yōu)勢,多種算法相輔相成,互為補充,才能構成一個完整的模糊智能控制系統(tǒng),為研究優(yōu)化控制領域的復雜問題提供了理論依據。
關鍵詞:人工智能;智能控制;無刷直流電機;模糊控制;優(yōu)化
中圖分類號:TM33;TP13 文獻標識碼:A 文章編號:1007-3175(2018)11-0001-04
Research Summary of Fuzzy Intelligent Control Algorithms for Brushless Direct Current Motor Under AI Rush
XU Jing-cheng1,2, LING Yun1,2, HOU Wen-hao1,2
(1 College of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China;
2 Key Laboratory for Electric Drive Control and Intelligent Equipment of Hunan Province, Zhuzhou 412007, China)
Abstract: In the research field of artificial intelligence, the implement method of intelligent control differs from one another. This paper concretely expounded the artificial intelligence, the brushless direct current (DC) motor speed control system and the fuzzy control, analyzed the research status and development prospect of the fuzzy control applied in the brushless DC motor speed control system and pointed out that there existed defects if depending on the experience selection of the fuzzy system parameters and rules. The only way was to combine with the advantages of different algorithm, made multiple algorithms supply with each other to construct a complete fuzzy intelligent control system, which provides the theoretical foundation for the complex problems of optimized control domain research.
Key words: artificial intelligence; intelligent control; brushless direct current motor; fuzzy control; optimization
參考文獻
[1] 李屹,李曦. 認知網絡中的人工智能[M]. 北京:北京郵電大學出版社,2014.
[2] 徐敬成, 凌云, 陳海東, 等. 無刷直流電機遠程調速控制方法[J]. 湖南工業(yè)大學學報,2017,31(1):52-55.
[3] 楊婕,王魯. 現(xiàn)代與智能控制技術[M]. 天津:天津大學出版社,2013.
[4] 徐敬成,凌云,侯文浩,等. 一種帶微分負反饋的無刷直流電機模糊優(yōu)化PI控制方法[J]. 新型工業(yè)化,2018,8(6):1-6.
[5] 陳茂林,劉知貴,范玉德,等. 注塑機注射速度的自組織模糊控制器設計[J]. 制造業(yè)自動化,2015,37(12):45-47.
[6] PANICKER D K. Hybrid PI-Fuzzy Controller for Brushless DC Motor Speed Control[J]. Journal of Electrical and Electronics Engineering,2013,8(6):33-43.
[7] LIN C M, HSU C F, YEH R G. Adaptive fuzzy sliding-mode control system design for brushless DC motors[J].International Journal of Innovative Computing Information & Control Ijicic,2013,9(3):1259-1270.
[8] 張大斌. 遺傳算法與模糊邏輯的融合設計及其應用[M]. 武漢:湖北科學技術出版社,2010.
[9] 蔡凌,翟助群,張纓,等. 基于模糊調整的變結構自適應PID控制器[J]. 兵工學報,2015,36(S2):280-284.
[10] PREMKUMAR K, MANIKANDAN B V.Adaptive Neuro-Fuzzy Inference System Based Speed Controller for Brushless DC Motor[J]. Neurocomputing,2014,138(11):260-270.
[11] 莫愿斌. 群智能算法及化工優(yōu)化問題[M]. 北京:北京理工大學出版社,2015.
[12] LEI J, DOU M.Adaptive Fuzzy Control for BLDCM in Near Space Based on RBF Neural Network Compensation[J]. Journal of Northwestern Polytechnical University,2014,32(3):394-399.
[13] 周立,古富龍. 改進遺傳優(yōu)化的無刷直流電機模糊PI控制[J]. 遼寧工程技術大學學報(自然科學版),2014,33(12):1679-1684.
[14] 王云良,王繼水,王敏其. 無刷直流電機自適應模糊優(yōu)化控制[J]. 電機與控制應用,2014,41(11):14-17.
[15] PREMKUMAR K, MANIKANDAN B V.Bat algorithm optimized fuzzy PD based speed controller for brushless direct current motor[J].Engineering Science and Technology, an International Journal,2016,19(2):818-840.
[16] 張禹,劉群,劉慧芳,王哲. 改進粒子群優(yōu)化的無刷直流電機模糊控制[J]. 組合機床與自動化加工技術,2017(10):101-104.
[17] GHANY M A A, SHAMSELDIN M A, GHANY A M A. A novel fuzzy self-tuning technique of single neuron PID controller for brushless DC motor[J].International Journal of Power Electronics & Drive Systems,2017,8(4):1705.