基于遗传-模糊算法的开关磁阻电机位置计算

采用智能方法实现开关磁阻电机的非线性建模及转子位置的精确估算．根据实验测得的开关磁阻电机定子电流、绕组电感和转子位置，得到开关磁阻电动机非线性特性．利用比特性得到模糊规则，实现开关磁阻电机的模糊建模；在此基础上，分别利用神经网络的学习和遗传算法全局优化算法，实现了精确和最优模糊建模．该方法可以实现转子位置的精确估计并具有一定鲁棒性和可靠性，可取代直接的位置传感器．利用智能建模可以避免非线性系统建模的复杂性．仿真结果证明了建模的有效性．

Position Calculation of Switched Reluctance Motors Based on Genetic Algorithm-Fuzzy Logic Method

Intelligent approaches were applied to the procedure of nonlinear modeling for switched reluctance motor (SRM) and exact estimation of the rotor position.From the measured data of stator current, winding inductance and rotor angle position in experiment, the nonlinear characteristic of SRM was obtained and fuzzy rules were further developed. Learning ability of neural network and global optimization of genetic algorithm(GA) was employed to minimize the modeling error.The proposed algorithm can realize exact estimation of the rotor position with certain robustness and reliability and can directly replace the sensor of position.Complexity can be avoided by intelligent modeling of nonlinear system.The results of simulation demonstrate efficiency of the modeling.