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Estimation of Heat Source Term and Thermal Diffusion in Tokamak Plasmas Using a Kalman Filtering Method in the Early Lumping Approach

机译:早期集总法中使用卡尔曼滤波方法估算托卡马克等离子体中的热源项和热扩散

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摘要

In this paper, early lumping estimation of space-time varying diffusion coefficient and source term for a nonhomogeneous linear parabolic partial differential equation (PDE) describing tokamak plasma heat transport is considered. The analysis of this PDE is achieved in a finite-dimensional framework using the cubic b-splines finite element method with the Galerkin formulation. This leads to a finite-dimensional linear time-varying state-space model with unknown parameters and inputs. The extended Kalman filter with unknown inputs without direct feedthrough (EKF-UI-WDF) is applied to simultaneously estimate the unknown parameters and inputs and an adaptive fading memory coefficient is introduced in the EKF-UI-WDF, to deal with time varying parameters. Conditions under which the direct problem is well posed and the reduced order model converges to the initial one are established. In silico and real data simulations are provided to evaluate the performances of the proposed technique.
机译:本文考虑了描述托卡马克等离子体传热的非均匀线性抛物型偏微分方程(PDE)的时空变化扩散系数和源项的早期集总估计。使用立方b样条有限元方法和Galerkin公式,在有限维框架内对PDE进行分析。这导致具有未知参数和输入的有限维线性时变状态空间模型。应用具有未知输入而没有直接馈通的扩展卡尔曼滤波器(EKF-UI-WDF)来同时估计未知参数和输入,并在EKF-UI-WDF中引入了自适应衰落存储系数,以处理随时间变化的参数。建立了直接问题能够很好地提出并且降阶模型收​​敛到初始模型的条件。提供计算机模拟和真实数据模拟以评估所提出技术的性能。

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