Indirect position detection of SRM based on genetic algorithm

Due indirect position detection of SRM based on traditional BP neural network have shortcomings of long training time, slow convergence and easy to fall into local minimum, this paper presents a method of indirect position detection based on BP neural network optimized by genetic algorithm. The method uses the global optimization ability of genetic algorithm(GA) to correct weights and thresholds of BP network, then uses the trained BP network to achieve the nonlinear mapping between the current, flux and rotor position of motor. Simulation results demonstrate that the genetic algorithm has a significant effect to improve performance of BP neural network, and improves the detection accuracy, then achieve indirect position detection of switched reluctance motor.