基于模糊RBF神经网络的柴油机电液调速控制方法  

The Research on RBF Fuzzy Neural Network of Electro-hydraulic Speed Governor System for Diesel Engine

作　　者：张大庆[1] 赖涤泉[1] 

机构地区：[1]石家庄铁道学院机械工程分院,河北石家庄050043

出　　处：《石家庄铁道学院学报》2007年第3期41-45,共5页Journal of Shijiazhuang Railway Institute

摘　　要：介绍了电液调速执行器的动态特性,设计了电液调速控制回路,实现了模糊RBF神经网络对柴油机油门执行器位置的控制。将一种基于模糊RBF神经网络的PID控制器应用于柴油机调速控制中,详细说明了模糊RBF神经网络控制器的设计过程,它结合了传统PID以及神经网络和模糊控制的优点,可以在线调整得到一组最优的PID控制参数。仿真结果表明该系统比传统模糊控制的响应速度快、超调小,且适应性强,具有推广价值。Serve-control of accelerator position for an electro-hydraulic speed governor of automotive diesel engine is studied based on RBF Fuzzy Neural Network control theory. The accelerator position for an electro-hydraulic speed governor of automotive diesel engine is introduced and its control loop is designed. A controller based on Fuzzy Neural Networks and PID control in accelerator position is presented for an electro-hydraulic speed governor. The design process of the RBF Fuzzy Neural Network control is introduced in detail. This controller which combines the advantages of the Fuzzy control and Neutral Networks control can get the best PID pa- rameters by self-adjustment on line The simulation study proves that this control system has a better adaptability and can improve the control effect greatly .

关 键 词：模糊控制 RBF神经网络 柴油机 电液调速 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]