摘要
为了优化两相混合式步进电机的速度控制,研究了步进电机强耦合磁场和时变参数对闭环控制系统的影响。依据步进电机运行原理和绕组反电势与转子位置的关系,提出了一种基于大脑情感学习模型的智能控制方法。该方法不依赖于被控对象的动态数学模型,因此避免了步进电机时变参数对模型准确性的影响。将该方法与常见的PID控制进行对比,结果表明:该方法能够更好地抑制运动过程中的抖动,加快电机的响应速度,提高速度跟踪精度,适用于对响应速度、精度和稳定性要求较高的场合。
In order to optimize the speed control performance of two-phase hybrid stepping motor, the impacts of the strong-coupled magnetic field and the time-varying parameters on the closed-loop control system are explored. According to the operating principle of stepping motor and relationship between winding back electromotive force and rotor position, an intelligent control method is proposed based on brain emotional learning model. This method is independent to the dynamic mathematical model of the motor, thus eliminating the effects of the time-varying parameters. Compared with Proportional Integral Derivative （PID） control, the proposed method can more effectively inhibit the vibration, increase the speed of response and improve the speed tracking precision. This control method is suitable for the applications with high requirements on response speed, precision and stability.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2014年第3期765-770,共6页
Journal of Jilin University:Engineering and Technology Edition
基金
陕西省科学技术研究发展计划项目(2007K05-06)
关键词
电气工程
混合式步进电机
大脑情感学习
速度控制
electrical engineering
hybrid stepping motor
brain emotional learning（BEL）
speed control
