DocumentCode :
2108860
Title :
Chaos Optimizing BP-NNG Speed Recognition in DTC System
Author :
Cao, Chengzhi ; Li, Fengkun ; Zhang, Kun ; Zhang, Hongbing ; San, Hongli
Author_Institution :
Coll. of Inf. Sci. & Eng., Shenyang Univ. of Techonolgy, Shenyang
fYear :
2008
fDate :
21-22 Dec. 2008
Firstpage :
1077
Lastpage :
1080
Abstract :
According to the non-linear relationship of direct torque control (DTC) system, multiorbit chaos optimizing algorithm is put forward, which resolve the slower converging problem of single-orbit and single-non-linearity-function chaos algorithm. In addition, the conception of neural network group (NNG) is proposed to resolve the bigger periodical errors problem. As the sub-network of NNG is intended to deal with different data group, the accuracy has been improved greatly. The result of DTC system simulation in MATLAB/SIMULINK shows that NNG speed recognition optimized by the multiorbit chaos optimizing algorithm has better tracking capability and fitness, as well as favorable static and dynamic properties.
Keywords :
backpropagation; chaos; control nonlinearities; neurocontrollers; torque control; velocity control; DTC system; MATLAB/SIMULINK; chaos optimizing BP-NNG speed recognition; linear direct torque control; multiorbit chaos optimizing algorithm; neural network group; periodical errors problem; single-nonlinearity-function chaos algorithm; single-orbit chaos algorithm; Ant colony optimization; Chaos; Design optimization; Educational institutions; Information science; Information technology; MATLAB; Neural networks; Nonlinear dynamical systems; Torque control; DTC; Neural Network Group (NNG); chaos; multiorbit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3505-0
Type :
conf
DOI :
10.1109/IITA.Workshops.2008.54
Filename :
4732124
Link To Document :
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