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标题：基于Elman神经网络观测器的永磁同步电机无传感器控制 |
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作者：孙凯翔 ,胡兆稳, 丁曙光，等 |
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| 2019年第5期 访问次数：1009次 |
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摘要： 针对永磁同步电机(PMSM)的无传感器控制问题，提出了一种基于Elman神经网络(ENN)观测器的PMSM无传感器控制方法。ENN适用于动态系统建模，并且所需的神经元数量少，收敛精确。根据ENN训练及电机无传感器控制特点，制定ENN在线训练策略，从而实现ENN观测器的自适应及电机转速、位置的准确估计。利用Lyapunov稳定性理论分析了ENN训练过程的稳定性。通过对机械参数扰动、负载扰动、电磁参数扰动的测试，验证了ENN观测器的有效性。仿真结果证明了所提出的ENN观测器具有优越的鲁棒性和精度。
关键词：永磁同步电机；无传感器控制；观测器；Elman神经网络
Abstract: An Elman Neural Network（ENN）based observer was proposed for the sensorless control of the Permanent Magnet Synchronous Motor (PMSM). The ENN, which captures the dynamic behavior of a system, requires fewer neurons and converges precisely. A novel online training strategy was formulated based on the characteristics of ENN training and the sensorless control of PMSM, which can realize the adaptation of the ENN based observer and the precise estimation of speed and position of PMSM. The stability of the ENN training process was analyzed using the Lyapunov stability theory. The performance of the ENN based observer was analysed under various factors such as mechanical parameter variations, load disturbance, electromagnetic parameter variations, which can influence the sensorless control performance of PMSM. As the simulation results demonstrate, the ENN based observer presented in this paper is highly robust and precise.
Key words: permanent magnet synchronous motor; sensorless control; observer; Elman neural network |
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