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Optimal Matching Control of a Low Energy Charged Particle Beam in Particle Accelerators

机译:粒子加速器中低能带电粒子束的最优匹配控制

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摘要

Particle accelerators are devices used for research in scientific problems such as high energy and nuclear physics.In a particle accelerator,the shape of particle beam envelope is changed dynamically along the forward direction.Thus,this reference direction can be considered as an auxiliary "time" beam axis.In this paper,the optimal beam matching control problem for a low energy transport system in a charged particle accelerator is considered.The beam matching procedure is formulated as a finite "time" dynamic optimization problem,in which the Kapchinsky-Vladimirsky (K-V) coupled envelope equations model beam dynamics.The aim is to drive any arbitrary initial beam state to a prescribed target state,as well as to track reference trajectory as closely as possible,through the control of the lens focusing strengths in the beam matching channel.We first apply the control parameterization method to optimize lens focusing strengths,and then combine this with the time-scaling transformation technique to further optimize the drift and lens length in the beam matching channel.The exact gradients of the cost function with respect to the decision parameters are computed explicitly through the state sensitivity-based analysis method.Finally,numerical simulations are illustrated to verify the effectiveness of the proposed approach.
机译:粒子加速器是用于研究诸如高能和核物理等科学问题的设备。在粒子加速器中,粒子束包络线的形状沿正向动态变化。因此,该参考方向可以视为辅助方向。本文考虑了带电粒子加速器中低能量传输系统的最优光束匹配控制问题。将光束匹配过程表述为有限的“时间”动态优化问题,其中Kapchinsky-Vladimirsky(KV)耦合包络方程对光束动力学进行建模。其目的是通过控制镜头聚焦强度,将任意初始光束状态驱动到规定的目标状态,并尽可能接近地跟踪参考轨迹我们首先应用控制参数化方法优化镜头聚焦强度,然后将其与时标转换结合起来。进一步优化了光束匹配通道中的漂移和透镜长度的技术。通过基于状态敏感度的分析方法,显式计算出成本函数相对于决策参数的精确梯度。最后,通过数值模拟验证了该方法的有效性。建议方法的有效性。

著录项

  • 来源
    《自动化学报(英文版)》 |2019年第2期|460-470|共11页
  • 作者单位

    School of Automation, Guang dong University of Technology, and Guangdong Key Laboratory of IoT Information Technology, Guangzhou 510006, China;

    Faculty of Mechanical Engineering and Mechanics, Ningbo University, Ningbo 315211, China;

    School of Automation, Guang dong University of Technology, and Guangdong Key Laboratory of IoT Information Technology, Guangzhou 510006, China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
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  • 入库时间 2022-08-19 04:26:58
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