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提出了一种基于模糊RBF神经网络的永磁同步电机DTC控制方案。该方案是在直接转矩控制系统的基础上,在模糊控制器前端加入了RBF神经网络模块,在对转矩误差、定子磁链误差和磁链角度进行映射前,对其进行数据处理获得合理的模糊分级,并作为模糊控制器的输入以便选择合理的电压空间矢量。RBF神经网络模块的加入使得系统具有更好的鲁棒性,仿真结果表明,基于模糊RBF神经网络的永磁同步电机DTC控制系统具有较好的动、静态性能,能够实现快速响应。
A DTC control scheme of permanent magnet synchronous motor based on fuzzy RBF neural network is proposed. The program is based on the direct torque control system, the RBF neural network module is added to the front of the fuzzy controller, the data processing is reasonable before the torque error, stator flux error and flux linkage angle are mapped Fuzzy classification, and as fuzzy controller input in order to select a reasonable voltage space vector. The addition of RBF neural network makes the system have better robustness. The simulation results show that the DTC control system of PMSM based on fuzzy RBF neural network has good dynamic and static performance and can respond quickly.