“智能管”大功率后向波振荡器的控制研究进展

E. Schamiloglu, G. Park, V. S. Soualian, C. Abdallah, Frank Hegeler
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引用次数: 1

摘要

先前关于强光束驱动的相对论反向波振荡器(BWO)的各种参数控制的成就包括在确定的频率带宽上保持指定或期望的输出功率,以及在很宽的功率范围内保持恒定的频率。这是通过迭代学习控制(ILC)算法完成的,该算法产生了电子束的适当输入变量,以及慢波结构从截止颈的适当位移。更复杂的问题是频率和功率的同时控制,涉及到功率和频率依赖于两个输入变量的独立映射:阴极电压和慢波结构位移。所得到的双变量系统已成功实现,并在最小迭代下进行了收敛性测试。在本文中,我们概述了我们的“智能管”,它的发展,和我们的最新成果。
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Advances in the control of a "smart tube" high power backward wave oscillator
Previous accomplishments pertaining to the control of various parameters of an intense beam-driven relativistic backward wave oscillator (BWO) include maintaining a specified or desired output power over a determined frequency bandwidth, and maintaining a constant frequency over a wide range of power. This was accomplished using an iterative learning control (ILC) algorithm that yielded the appropriate input variables for the electron beam, as well as the appropriate displacement of the slow wave structure from the cutoff neck. A problem of much greater complexity is the simultaneous control of both frequency and power, involving the independent mapping of both power and frequency dependence on the two input variables: cathode voltage and slow wave structure displacement. The resultant two-variable system has been successfully implemented and tested for convergence with minimal iterations. In this paper we present an overview of our "smart tube," its development, and our most recent results.
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