DocumentCode
423893
Title
Optimization design of fuzzy neural network controller in direct torque control system
Author
Cao, Cheng-Zhi ; Wei, Guang-Hua ; Zhang, Qedong ; Wang, Xin
Author_Institution
Sch. of Inf. Sci. & Eng., Shenyang Univ. of Technol., Liaoning, China
Volume
1
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
378
Abstract
How to correctly select the voltage space vector in a direct torque control system is one of the key techniques to get over the shortcoming of the DTC system at low speed. We introduce the intelligent optimization algorithm to the fuzzy neural network controller adopted by the direct torque control system. Adopting the immune genetic algorithm to optimize the weights and grade of the membership function of the fuzzy neural network can get over the defects that are easy to get in the local minima of BP. It can infer with the stator voltage vector reasonably. It has an easy control system, a dynamic torque response, and a fast rotation speed. It improves the low speed performances of the direct torque system.
Keywords
fuzzy control; genetic algorithms; induction motors; intelligent control; machine control; neurocontrollers; torque control; asynchronous motors; direct torque control system; dynamic torque response; fuzzy neural network controller; immune genetic algorithm; intelligent control; intelligent optimization algorithm; optimization design; stator voltage vector; voltage space vector; Control systems; Design optimization; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Intelligent networks; Stators; Switches; Torque control; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1380712
Filename
1380712
Link To Document