摘要
针对超声波电机参数的时变性、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波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波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.
Focusing on features of ultrasonic motor including time-varying parameters, non-linear system and strong coupling, the paper introduces fuzzy neural network control strategy for ultrasonic motor speed based on immune genetic algorithm. The results show that, the new approach can realize the adaptive tracking of the ultrasonic motor speed model compared with traditional fuzzy neural network speed control. It has the advantages of small response speed pulse, flexible control, adaptability, high control precision and robustness.
出处
《深圳职业技术学院学报》
CAS
2009年第3期19-22,共4页
Journal of Shenzhen Polytechnic
基金
江苏广播电视大学学术带头人基金资助项目
关键词
免疫遗传算法
超声波电机
模糊神经网络
速度控制
immune genetic algorithm
ultrasonic motors
fuzzy neural network
speed control
