DocumentCode :
1890919
Title :
Parameter Identification of PMSM Based on FHPSO Algorithm
Author :
Qian Miao-wang ; Tan Guo-Jun ; Ling Zang
Author_Institution :
Sch. of Inf. & Electr. Eng., China Univ. of Min. & Technol., Xuzhou, China
fYear :
2010
fDate :
25-26 Dec. 2010
Firstpage :
1
Lastpage :
4
Abstract :
A new fuzzy hybrid particle swarm optimization algorithm (FHPSO) is presented in the paper for parameter identification of permanent magnet synchronous motor (PMSM).The FHPSO algorithm uses hybrid optimal model which is obtained by the combination of global optimal model and local optimal model.And for the disadvantages of basic particle swarm optimization (BPSO) and fuzzy particle swarm optimization (FPSO) algorithm proposed by former researchers,a new fuzzy control method for inertia weight is presented.The results of comparison between BPSO,FPSO and FHPSO algorithms show that the FHPSO algorithm has better capacity than other 2 algorithms.In addition,the results of parameter identification indicate that the algorithm has good performances on different noise levels. Therefore,the FHPSO algorithm is viable for parameter identification of PMSM.
Keywords :
fuzzy control; machine control; particle swarm optimisation; permanent magnet motors; synchronous motors; BPSO; FHPSO algorithm; FPSO; PMSM; fuzzy control; fuzzy hybrid particle swarm optimization; global optimal model; hybrid optimal model; inertia weight; local optimal model; parameter identification; permanent magnet synchronous motor; Fuzzy control; Noise level; Optimization; Parameter estimation; Particle swarm optimization; Permanent magnet motors; Prediction algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
Conference_Location :
Wuhan
ISSN :
2156-7379
Print_ISBN :
978-1-4244-7939-9
Electronic_ISBN :
2156-7379
Type :
conf
DOI :
10.1109/ICIECS.2010.5677904
Filename :
5677904
Link To Document :
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