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
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