摘要
针对超声电机参数的时变性、系统内在的非线性和系统的强耦合性等特点,提出基于免疫遗传算法的超声电机模糊神经网络速度控制策略.实验结果表明,与传统模糊神经网络速度控制相比,采用该方法的系统能较好地实现设定的超声电机速度参考模型的自适应跟踪,响应速度脉动小,具有控制灵活、适应性强、控制精度高、鲁棒性强等优点.
Based on the time varying parameters, nonlinear and strong coupling features of Ultrasonic Motor, a fuzzy neural network control strategy for ultrasonic motor speed based on immune genetic algorithm is pointed out in this paper. Results show that systems using this method can be well set to achieve the speed of ultrasonic motor model reference adaptive tracking compared with the traditional fuzzy neural network speed control. It has small response speed pulse, flexible control, good adaptability, high control precision and robusthess.
出处
《厦门理工学院学报》
2009年第2期30-34,共5页
Journal of Xiamen University of Technology
关键词
免疫遗传算法
超声电机
模糊神经网络
速度控制
immune genetic algorithm
ultrasonic motors
fuzzy neural network
speed control
