摘要
在横梁运输网络(隧道) 的光圈混乱控制的题目为高水流的质子横梁 since1990' 的许多重要应用程序成为了一个关键担心的问题。在这篇论文，磁场适应控制基于神经网络，推迟 withtime 的反馈为与周期的集中的隧道在横梁运输网络压制横梁光圈混乱被建议。高水流的质子横梁的信封半径被控制由合适选择控制结构和神经网络的参数到达匹配的横梁半径，调整延期时间和神经网络的控制系数。
Subject of the halo-chaos control in beam transport networks （channels） has become a key concerned issue for many important applications of high-current proton beam since 1990＇. In this paper, the magnetic field adaptive control based on the neural network with time-delayed feedback is proposed for suppressing beam halo-chaos in the beam transport network with periodic focusing channels. The envelope radius of high-current proton beam is controlled to reach the matched beam radius by suitably selecting the control structure and parameter of the neural network, adjusting the delayed-time and control coefficient of the neural network.
基金
The project supported by the Key Projects of National Natural Science Foundation of China under Grant No. 70431002 and National Natural Science Foundation of China under Grants Nos. 70371068 and 10247005
关键词
神经网络
适应
时滞反馈
传输网络
周期聚焦通道
质子束
混沌控制
beam transport network, periodic focusing channels, high-current proton beam, halo-chaos, neural network adaptation control, time-delayed feedback
