Volume 7 Number 5 (May. 2012)
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JSW 2012 Vol.7(5): 966-973 ISSN: 1796-217X
doi: 10.4304/jsw.7.5.966-973

A Novel MC-DTC Method for Induction Motor Based on Fuzzy-neural Network Space Vector Modulation

Bin-jun Cai1, 2 and Xiao-hong Nian1

1School of Information Science and Engineering, Central South University, Changsha, China
2Hunan Institute of Engineering, Xiangtan, China

Abstract—To improve the low speed performance of the direct torque control(DTC) system. The advantages of DTC method are combined with the advantages of the matrix converter based on space vector modulation technique. The design process of the neural network controller which generating the flux reference voltage vector and fuzzy controller which applying the torque reference voltage vector were represented. This proposed novel method provides a precious input power factor control capability beside the high control performances. Furthermore, Conventional principles of DTC and space vector modulation(SVM) of matrix converter(MC) were described. The combination of the two was given in detail. Finally, the simulation and experiment research were carried out to identify the new method effectiveness. The results of induction motor control at both steady state and transient state are shown to improve the low-speed performance and strong adaptabiIity of novel control strategy.

Index Terms—DTC;MC;SVM;Fuzzy-neural network; lowspeed performance


Cite: Bin-jun Cai and Xiao-hong Nian, "A Novel MC-DTC Method for Induction Motor Based on Fuzzy-neural Network Space Vector Modulation," Journal of Software vol. 7, no. 5, pp. 966-973, 2012.

General Information

  • ISSN: 1796-217X (Online)
  • Frequency:  Quarterly
  • Editor-in-Chief: Prof. Antanas Verikas
  • Executive Editor: Ms. Yoyo Y. Zhou
  • Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
  • E-mail: jsweditorialoffice@gmail.com
  • APC: 500USD
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