Abstract: Focusing on some disadvantages in standard BP algorithm, such as low convergence rate, easily falling into local minimum point and weak global search capability, Genetic algorithm is used to optimal the connection weight of BP Algorithm in this paper, and construct a GA-BP algorithm of evolutionary neural network, and the algorithm is applied to the control of BLDCM speed adjusting system. The results of simulations shown: contrast to the traditional PI control system it has the advantage of no surplus regulation. Contrast to BP algorithm, it has a high convergence rate and not easily falling into local minimum point.

Key words: BLDCM, Evolutionary Neural Network, Genetic Algorithm, BP Network, Speed Control

摘要： 针对标准BP算法存在全局搜索能力弱和易陷入局部极小点等缺点，本文将遗传算法与BP神经网络相结合，构造了一种新的进化神经网络GA-BP算法，并将该算法应用于无刷直流电机调速系统的控制，仿真结果表明，与传统的PI控制系统相比，该算法得出的电机控制曲线几乎无超调，与基于BP算法的速度控制系统相比较，具有收敛速度快、不易陷入局部极小的优点。

关键词: 无刷直流电机, 进化神经网络, 遗传算法, BP网络, 速度控制