基于多重神经网络和负载转矩观测器的FOC策略的永磁同步电机无传感器控制

M. Nicola, C. Nicola, M. Duta
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引用次数: 9

摘要

本文介绍了永磁同步电机(PMSM)的无传感器控制系统,其中速度控制器由多人工神经网络(M-ANN)组成,转子速度由滑模观测器(SMO)提供。并与传统的场定向控制(FOC)系统进行了比较。负载转矩观测器的实现允许选择经过特殊训练的相应人工神经网络,以在负载转矩变化范围内获得最佳性能。给出了永磁同步电动机方程、转速和负载转矩观测器方程、主要模块和控制结构及其参数化和数值仿真结果。利用常用的Simulink和Stateflow模块进行了数值仿真,得到了良好的结果,可以在嵌入式系统中实现,表明所提出的永磁同步电机控制系统是实时实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sensorless Control of PMSM using FOC Strategy Based on Multiple ANN and Load Torque Observer
This article presents the sensorless control system of a Permanent Magnet Synchronous Motor (PMSM), where the speed controller consists of a Multiple - Artificial Neural Networks (M-ANN) and the rotor speed is provided by a Sliding Mode Observer (SMO). The performance of the proposed control system is presented in comparison with the classic Field Oriented Control (FOC) system. The implementation of a load torque observer allows the selection of a specially trained corresponding ANN to obtain optimum performance over the load torque variation ranges. The PMSM equations, the speed and load torque observers equations, the main blocks and control structures, their parameterizations and the results of the numerical simulations obtained are presented. The good results obtained as a result of the numerical simulations involving the use of the usual Simulink and Stateflow blocks, which can be implemented in embedded systems recommend the real-time implementation of the proposed PMSM control system.
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