论文标题

使用先进的可编程电源对MST的环形磁场和等离子体电流的同时反馈控制

Simultaneous feedback control of toroidal magnetic field and plasma current on MST using advanced programmable power supplies

论文作者

Goumiri, I. R., McCollam, K. J., Squitieri, A. A., Holly, D. J., Sarff, J. S., Leblanc, S. P.

论文摘要

电感电场的可编程控制能够在麦迪逊对称的圆环(MST)设备中进行反向场捏(RFP)等离子体的高级操作,并进一步为俄亥俄州加热的融合融合RFP等离子体开发了技术基础。 MST的Poloidal和Toroidal磁场($ b_ \ text {p} $和$ b_ \ text {t} $)可以通过基于集成的山脉双极晶体管(IGBT)的可编程电源(PPSS)来源。为了提供对$ b_ \ text {p} $和$ b_ \ text {t} $电路的实时同时控制,开发了一个独立的集成模型。用于控制的执行器是$ b_ \ text {p} $和$ b_ \ text {t} $由PPSS产生的主要电流。控制系统目标将是跟踪可以在等离子体表面($ r = a $)进行测量的两个特定需求量的数量:等离子电流,$ i_ \ text {p} \ sim b_ \ sim b_ \ text {p} $,rfp reverser comporter,$ f \ sim b_ b_ \ sim b_ \ tort tor tor tor e portor e per a $ 等离子体。边缘安全系数,$ q(a)\ propto b_t(a)$,倾向于跟踪$ f $,但不是相同的。为了了解$ i_ \ text {p} $和$ f $对执行器的响应,并启用控制算法的系统设计,运行了专用实验,其中调制了执行器,并使用系统识别方法生成了线性化的动态数据驱动模型。我们执行一系列初始实时实验来测试设计的反馈控制器并验证派生的模型预测。反馈控制器显示出对简单的进发控制器的系统改进。

Programmable control of the inductive electric field enables advanced operations of reversed-field pinch (RFP) plasmas in the Madison Symmetric Torus (MST) device and further develops the technical basis for ohmically heated fusion RFP plasmas. MST's poloidal and toroidal magnetic fields ($B_\text{p}$ and $B_\text{t}$) can be sourced by programmable power supplies (PPSs) based on integrated-gate bipolar transistors (IGBT). In order to provide real-time simultaneous control of both $B_\text{p}$ and $B_\text{t}$ circuits, a time-independent integrated model is developed. The actuators considered for the control are the $B_\text{p}$ and $B_\text{t}$ primary currents produced by the PPSs. The control system goal will be tracking two particular demand quantities that can be measured at the plasma surface ($r=a$): the plasma current, $I_\text{p} \sim B_\text{p}(a)$, and the RFP reversal parameter, $F\sim B_\text{t}(a)/Φ$, where $Φ$ is the toroidal flux in the plasma. The edge safety factor, $q(a)\propto B_t(a)$, tends to track $F$ but not identically. To understand the responses of $I_\text{p}$ and $F$ to the actuators and to enable systematic design of control algorithms, dedicated experiments are run in which the actuators are modulated, and a linearized dynamic data-driven model is generated using a system identification method. We perform a series of initial real-time experiments to test the designed feedback controllers and validate the derived model predictions. The feedback controllers show systematic improvements over simpler feedforward controllers.

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