基于WOA-ESN的电机系统混沌振荡预测

doi:10.19596/j.cnki.1001-246x.8442

摘要/Abstract

摘要：

提出一种将鲸鱼优化算法(WOA)与回声状态网络算法(ESN)结合的WOA-ESN预测方法, 并将此方法应用到永磁同步电机(PMSM)的混沌振荡预测, 进行实验仿真并和其他预测算法比较, 证明所提出方法拥有更高的预测精度。

Abstract:

We propose a WOA-ESN model, which combines Whale Optimization Algorithm(WOA) with Echo State Network(ESN) and applie to the prediction chaos of Permanent Magnet Synchronous Motor(PMSM). WOA-ESN model was compared with ESN and PSO-ESN. It shows that the method has better prediction performance.

Key words: permanent magnet synchronous motor, echo state network, whale optimization algorithm, chaotic prediction

刘凯歌, 韦笃取. 基于WOA-ESN的电机系统混沌振荡预测[J]. 计算物理, 2022, 39(4): 498-504.

Kai-ge LIU, Du-qu WEI. Chaos Prediction of Motor System Based on WOA-ESN[J]. Chinese Journal of Computational Physics, 2022, 39(4): 498-504.

图/表 9

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Method	MSE	Time/s
ESN	4.45 × 10^-2	31
PSO-ESN	9.89 × 10^-3	957
WOA-ESN	5.23 × 10^-3	796

Method	MSE	Time/s
ESN	4.45 × 10^-2	31
PSO-ESN	9.89 × 10^-3	957
WOA-ESN	5.23 × 10^-3	796

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