Journal of System Simulation
Abstract
Abstract: High accuracy identification of parameters in Permanent magnet synchronous motor (PMSM) is the basis of controller design. According to the drawbacks of slow speed, big error, and small number of parameters in particle swarm optimization (PSO), least square method, and classical coral reefs optimization (CRO), an improved CRO with Cauchy and Gaussian mutation is proposed to solve the parameter identification problem in PMSM. The mathematical model of PMSM in dq coordinate system is established. The Cauchy and Gaussian mutation operator is introduced to CRO. Both of the two versions are applied for identifying parameters in PMSM, and are verified in Matlab/Simulink for comparison. The simulation results indicate that the improved CRO algorithm is able to improve the identification accuracies of stator resistance, d-axis inductance, q-axis inductance, and rotor flux; and guarantee the performance improvement in PMSM.
Recommended Citation
Wu, Dinghui; Xu, Huang; Quan, Yawei; and Ji, Zhicheng
(2019)
"Parameter Identification of Permanent Magnet Synchronous Motor Based on Mutation Coral Reef Algorithm,"
Journal of System Simulation: Vol. 30:
Iss.
8, Article 25.
DOI: 10.16182/j.issn1004731x.joss.201808025
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol30/iss8/25
First Page
3024
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.201808025
Last Page
3032
CLC
TM391.9
Recommended Citation
Wu Dinghui, Huang Xu, Quan Yawei, Ji Zhicheng. Parameter Identification of Permanent Magnet Synchronous Motor Based on Mutation Coral Reef Algorithm[J]. Journal of System Simulation, 2018, 30(8): 3024-3032.
DOI
10.16182/j.issn1004731x.joss.201808025
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