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Parameter Identification of PMSM Based on FHPSO Algorithm

机译:基于FHPSO算法的PMSM参数辨识。

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摘要

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.
机译:提出了一种新的模糊混合粒子群优化算法(FHPSO),用于永磁同步电动机(PMSM)的参数辨识。针对以前研究人员提出的基本粒子群算法(BPSO)和模糊粒子群算法(FPSO)的缺点,提出了一种新的惯性权值模糊控制方法。BPSO,FPSO和FHPSO算法的比较结果表明: FHPSO算法比其他两种算法具有更好的容量。此外,参数识别结果表明该算法在不同的噪声水平下具有良好的性能。因此,FHPSO算法对于PMSM的参数辨识是可行的。

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