Design calculations for fast plasma position control in Korea Superconducting Tokamak Advanced Research

“…3,4 Vertical elongation of the plasma column due to increasing of plasma current and decreasing of MHD instability are among interesting topics in relevant plasma research. 3,5 To control the vertical position of the plasma column, a compromising approach should be provided between these two mechanisms. This can be achieved using a closed loop control structure which adjusts the currents of Z position feedback coils.…”

Section: Introductionmentioning

confidence: 99%

“…This can be achieved using a closed loop control structure which adjusts the currents of Z position feedback coils. 3,5 Lately due to nonlinear dynamics of plasma displacement, several approaches like classical 6 and intelligent [7][8][9] adaptive controllers have been proposed. 10 In recent decades, neural networks (NN) with nonlinear structure and learning capability have been developed as new routes to obtain desired closed loop control in nonlinear problems.…”

Section: Introductionmentioning

confidence: 99%

Identification and control of plasma vertical position using neural network in Damavand tokamak

Rasouli

Koohi

2013

Review of Scientific Instruments

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In this work, a nonlinear model is introduced to determine the vertical position of the plasma column in Damavand tokamak. Using this model as a simulator, a nonlinear neural network controller has been designed. In the first stage, the electronic drive and sensory circuits of Damavand tokamak are modified. These circuits can control the vertical position of the plasma column inside the vacuum vessel. Since the vertical position of plasma is an unstable parameter, a direct closed loop system identification algorithm is performed. In the second stage, a nonlinear model is identified for plasma vertical position, based on the multilayer perceptron (MLP) neural network (NN) structure. Estimation of simulator parameters has been performed by back-propagation error algorithm using Levenberg-Marquardt gradient descent optimization technique. The model is verified through simulation of the whole closed loop system using both simulator and actual plant in similar conditions. As the final stage, a MLP neural network controller is designed for simulator model. In the last step, online training is performed to tune the controller parameters. Simulation results justify using of the NN controller for the actual plant.

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“…Some examples are taken including the classical method by using the EM theory, the simulation based on ANSYS with the preprocessing results from the DINA code, the calculation using the TYPHOON code with magnetic field, etc. [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

An approach to explore the eddy currents of the new type divertor for EAST device using ANSYS code

Liu

Yao

Doody

et al. 2013

Sci. China Technol. Sci.

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An effective method for eddy current calculation has been developed for EAST's new divertor by using ANSYS. A 3D model of a double null divertor for the EAST device was built to evaluate eddy currents and electromagnetic (EM) forces on these components. The main input to the model is the plasma current and poloidal field coil currents, which are loaded into the model using experimental data measured from the EAST discharges. These currents generate magnetic fields that match those producing an EAST discharge, and the time variation of these fields produces the eddy currents in the divertors, along with from the resulting EM forces. In addition, the first 10 time steps were discussed for the eddy current generation and changing trend. It indicates that a static analysis before a transient mode start can solve the eddy current origination in the initial time steps. With this method, the EM transient response of EAST's new divertor can be predicted based on ANSYS simulations. Furthermore, the method is also an effective approach to estimate the EM results for the in-vessel components of a fusion reactor during a disruption.

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Design calculations for fast plasma position control in Korea Superconducting Tokamak Advanced Research

Cited by 18 publications

References 12 publications

Newly developed double neural network concept for reliable fast plasma position control

Newly developed double neural network concept for reliable fast plasma position control

Identification and control of plasma vertical position using neural network in Damavand tokamak

An approach to explore the eddy currents of the new type divertor for EAST device using ANSYS code

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