摘要
设计一种基于自适应模糊神经网络原理的永磁同步电机电梯曳引机速度控制器.这种控制器具有神经网络自学习能力和模糊控制器处理不确定信息的能力.网络初始参数通过离线训练方式获得,从而实现对电机速度的智能控制.将模糊神经网络(fuzzy neural network control,FNNC)速度控制器与常用的PI控制、模糊PI控制方式对比进行仿真研究.研究表明,采用自适应模糊神经网络的控制器比另外两种方法更具有良好的鲁棒性和动态性能.
This paper presents a self-adaptive fuzzy neural network based on the principle of PMSM speed controller elevator traction machine. The controller has the learning ability of neural network and fuzzy controller from handling uncertain information. Initial parameters of the network are obtained through offline training mode, to implement intelligent control of motor speed. Compared between the FNNC PI speed controller with the common PI control and fuzzy PI control method by simulation study, the results show that the FNNC controller is more robust and better dynamic characteristics than the other two methods.
出处
《北京建筑工程学院学报》
2010年第3期57-60,共4页
Journal of Beijing Institute of Civil Engineering and Architecture
基金
北京市教委科技发展计划面上资助项目(KM200710016008)
