基于模糊神经网络的磁浮车悬浮控制器  

Suspension system of maglev train based on fuzzy neural network controller

作　　者：孙荣斌[1] 王鑫[1] 夏加宽[1] 

机构地区：[1]沈阳工业大学电气工程学院,辽宁沈阳110023

出　　处：《机电工程》2008年第1期86-88,92,共4页Journal of Mechanical & Electrical Engineering

摘　　要：以EMS型磁悬浮车单电磁铁为研究对象,建立了系统的数学模型。为增强悬浮系统的抗干扰能力和负载能力,针对其非线性特性,采用神经网络和模糊控制理论相结合的方法设计了非线性控制器FNNC。该控制器继承了模糊控制鲁棒性强以及神经网络的非线性逼近和自学习能力,运用加速反传训练方法对参数进行调整,并通过TMS320F2812型DSP实现单点悬浮用。实验及仿真表明,该控制器使系统悬浮稳定,动态性能好,与传统的PID控制器相比具有更好的快速跟踪性能和抗干扰能力。The single electromagnet of EMS maglev train was chosen to be the controlled object. The nonlinear mathematic model of electromagnetic suspension system was derived. In order to improve the ability of disturbance rejection and load, considering the nonlinear characteristic, an non-linear controller FNNC was designed which combined the neural network and the fuzzy control theory. FNNC inherited the robust characteristic of fuzzy control and the strong ability of nonlinear processing and self-learning of neural network. The training method of aecelcrating back-propagation algorithm was used to adjust the parameter. Single-point suspension was realized through TMS3200F2812 DSP. The test and emulation results show that the suspension point is stable and the performance of dynamic is good. FNNC is preferable to PID controller in respect of fast tracking performance and disturbance rejection performance.

关 键 词：磁悬浮列车 非线性 模糊神经网络 数字信号处理器 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]