基于遗传神经网络的伺服电机转速控制

AC Servo-Motor Speed Control Based on Genetic Neural Network

针对交流伺服控制的高速度和高精度,传统控制方法很难对其实施有效控制,给出一种基于遗传神经网络的控制策略。神经网络的结构和初始权值运用递阶遗传算法离线优化,并对电机参数进行实时辨识,通过辨识结果计算控制量,对电机进行实时控制。实验结果证明,该控制系统具有较高的控制精度和稳定性。

It was hard to apply the traditional control into AC servo control because of its high speed and accuracy. An adaptive control strategy of radial basis function neural network （RBFNN） was introduced. The construction and initial parameter was optimized by means of hybrid hierarchical genetic algorithm out of line. The motor was controlled in real time through the computation based upon the distinguished results. The experiment results proved the remarkable precision and stability of this control sycstem