Parameter Identification of Permanent Magnet Synchronous Motor Based on Mutation Coral Reef Algorithm

doi:10.16182/j.issn1004731x.joss.201808025

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.

Key words: coral reefs optimization, permanent magnet synchronous motor, parameter identification, Cauchy and Gaussian mutation

CLC Number:

TM391.9

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.

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