节点文献
驼峰速度控制系统中神经网络方法的研究
A STUDY OF HUMPING SPEED CONTROL SYSTEMS WITH NEURAL NETWORKS
【摘要】 现有的各种驼峰速度控制系统大多属开环系统,本文将神经网络学习算法引入速度控制系统达到系统闭环的效果。提出了一种直接控制的自适应神经元模型和神经网络结构,以及一种快速学习算法(FLA),并把该神经网络和算法用于驼峰速度控制系统。计算机模拟结果表明该算法是十分有效的
【Abstract】 It is well known that most of existing humping speed control systems are contained based on the open loop control systems.In this paper,a neural network learning algorithm method is introduced to the speed control systems to realize the closed loop control.A class of neural networks containing direct controlled adaptive neuron and the corresponding fast learning algorithm method are proposed for developing this new humping speed control system.The simulated results by computer show that the methods are very effective.
- 【文献出处】 铁道学报 ,JOURNAL OF THE CHINA RAILWAY SOCIETY , 编辑部邮箱 ,1996年05期
- 【分类号】V284.663
- 【被引频次】8
- 【下载频次】62