一种混合步进电机优化波形控制器设计

设计了一种基于人工神经网络的步进电机驱动电压波形控制器，对步进电机原有的驱动控制电压脉冲进行修正，提高步进电机的运行速度稳定度，该方案使用人工神经网络模拟输入输出样本即角位移与电压脉冲的映射关系，使经过训练后的网络对非样本输入有好的泛化能力；该方案只使用步进电机测量角位移不需要精确获取电机内部参数，实验证明，该驱动电压波形控制器方案是一种快速、简便、有效的设计，对电机低速空载和负载效应下的速度稳定度都有好的提高。

Optimum Driving Voltage Waveforms Controller Design for Two-Phase Hybrid Stepping Motor Based on Artificial Neural Network

This paper presents a driving voltage waveforms controller design scheme for stepping motor using artificial neural network, via amending the original driving voltage pulse to improve the rate stability of the stepping motor. ANN is used for identifying the relation- ship between the rotor angle position as input of ANN and voltage pulse as output, can provide well generalization ability for the non-sample data input. No other precision knowledge of motor parameters is required in this controller except the rotor angle position measurement. The experiments has proved this driving voltage controller is a fast, simple, effective design. It is helpful improving the rate stability of the stepping motor under low speed and both in non-load and on-load situation.