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Speed Estimation and Control of IPMSM Drive with HAI Controller  

Lee Hong-Gyun (순천대 공대 정보통신공학부)
Lee Jung-Chul (순천대 공대 정보통신공학부)
Chung Dong-Hwa (순천대 공대 정보통신공학부)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers D / v.54, no.4, 2005 , pp. 220-227 More about this Journal
Abstract
This paper presents hybrid artificial intelligent(HAI) controller based on the vector controlled IPMSM drive system. And it is based on artificial technologies that adaptive neural network fuzzy(A-NNF) is to speed control and artificial neural network(ANN) is to speed estimation. The salient feature of this technique is the HAI controller The hybrid action tolerates any inaccuracies in the fuzzy logic assignment rules or in the neural network stationary weights. Speed estimators using feedforward multilayer and artificial neural network(ANN) are compared. The back-propagation algorithm is easy to derived the estimated speed tracks precisely the actual motor speed. This paper presents the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control.
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1 K. J. Astron and B. Wittenmark, 'Adaptive control,' Addison-Wesley, 1989
2 F. Z. Feng, T. Fukao, 'Robust speed identification for speed sensorless vector control of induction motors,' IEEE Trans. on IA, vol. 30, no. 5, pp. 1234-1240, 1994   DOI   ScienceOn
3 H. Kubota and K. Matsuse, 'Speed sensorless field oriented control of induction motor with rotor resistance adaption,' IEEE Trans. on IA, vol. 30, no.5, pp. 1219-1224, 1994   DOI   ScienceOn
4 C. Schauder, 'Adaptive speed identification for vector control of induction motors,' IEEE Trans. on IA, pp. 1054-1061, 1992   DOI   ScienceOn
5 K. S. Narendra and K. Parthasarthy, 'Identification and control of dynamical system using neural network,' IEEE Trans. Neural Networks, Vol. 1, No. 1, pp. 4-27, 1990   DOI
6 I. J. Leontaritis and S. A. Billings, 'Input-output parametric models for nonlinear systems,' Int. J. Contr., vol. 41, pp. 303-344, 1985   DOI
7 M. G. Simoes and B. K. Bose, 'Neural network based estimation of feedback signals for a vector controlled induction motor drive,' IEEE Trans. IA, Vol. 31, No.3, pp. 620-629, 1995   DOI   ScienceOn
8 M. T. Wishart and R. G. Harley, 'Identification and control of induction machines using neural networks,' IEEE Trans. IA, Vol. 31, No.3, pp. 612-619, 1995   DOI   ScienceOn
9 Cybenko, 'Approximations by superposition of a sigmoidal function,' Mathematics of Contr., Signals and Syst., vol. 2, pp. 303-314, 1989   DOI
10 A. K. Toh, E. P. Nowicki and F. Ashrafzadeh, 'A flux estimator for field oriented control of an induction motor using an artificial neural network,' IEEE IAS Conf. Rec. Ann. Meet., Vol. 1, pp. 585-592, 1994   DOI
11 D. H. Chung, 'Fuzzy control for high performance vector control of PMSM drive system,' KIEE, vol. 47, no. 12, pp. 2171-2180, 1998