Finite-word-length FPGA implementation of model predictive control for ITER resistive wall mode control

•A fast implementation of model predictive control is presented.•The primal fast gradient method is used for online optimization.•Finite-word-length arithmetic is efficient for FPGA implementation.•A high-level synthesis approach for FPGA programming is used.•The approach is tested using a Xilinx Al...

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Published inFusion engineering and design Vol. 169; p. 112480
Main Authors Gerkšič, Samo, Pregelj, Boštjan
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.08.2021
Elsevier Science Ltd
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Online AccessGet full text
ISSN0920-3796
1873-7196
DOI10.1016/j.fusengdes.2021.112480

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Abstract •A fast implementation of model predictive control is presented.•The primal fast gradient method is used for online optimization.•Finite-word-length arithmetic is efficient for FPGA implementation.•A high-level synthesis approach for FPGA programming is used.•The approach is tested using a Xilinx Alveo U250 accelerator card. In advanced tokamak scenarios, active feedback control of unstable resistive wall modes (RWM) may be required. A RWM is an instability due to plasma kink at higher plasma pressure, moderated by the presence of a resistive wall surrounding the plasma. We address the dominant kink instability associated with the main non-axisymmetric (n = 1) RWM, described by the CarMa model. Model predictive control (MPC) is used, with the aim of enlarging the domain of attraction of the unstable RWM modes subject to power-supply voltage constraints. The implementation of MPC is challenging, because the related quadratic programming (QP) on-line optimization problems must be solved at a sub-ms sampling rate. Using complexity-reduction pre-processing techniques and a primal fast gradient method (FGM) QP solver, sufficiently short computation times for ITER are reachable using a standard personal computer (PC). In this work we explore even faster finite-word-length (FWL) implementation using field-programmable gate arrays (FPGA), which would facilitate experimental testing of such control algorithms on dynamically faster medium-sized tokamaks, and compare the computational accuracy and time with the PC implementation.
AbstractList In advanced tokamak scenarios, active feedback control of unstable resistive wall modes (RWM) may be required. A RWM is an instability due to plasma kink at higher plasma pressure, moderated by the presence of a resistive wall surrounding the plasma. We address the dominant kink instability associated with the main non-axisymmetric (n = 1) RWM, described by the CarMa model. Model predictive control (MPC) is used, with the aim of enlarging the domain of attraction of the unstable RWM modes subject to power-supply voltage constraints. The implementation of MPC is challenging, because the related quadratic programming (QP) on-line optimization problems must be solved at a sub-ms sampling rate. Using complexity-reduction pre-processing techniques and a primal fast gradient method (FGM) QP solver, sufficiently short computation times for ITER are reachable using a standard personal computer (PC). In this work we explore even faster finite-word-length (FWL) implementation using field-programmable gate arrays (FPGA), which would facilitate experimental testing of such control algorithms on dynamically faster medium-sized tokamaks, and compare the computational accuracy and time with the PC implementation.
•A fast implementation of model predictive control is presented.•The primal fast gradient method is used for online optimization.•Finite-word-length arithmetic is efficient for FPGA implementation.•A high-level synthesis approach for FPGA programming is used.•The approach is tested using a Xilinx Alveo U250 accelerator card. In advanced tokamak scenarios, active feedback control of unstable resistive wall modes (RWM) may be required. A RWM is an instability due to plasma kink at higher plasma pressure, moderated by the presence of a resistive wall surrounding the plasma. We address the dominant kink instability associated with the main non-axisymmetric (n = 1) RWM, described by the CarMa model. Model predictive control (MPC) is used, with the aim of enlarging the domain of attraction of the unstable RWM modes subject to power-supply voltage constraints. The implementation of MPC is challenging, because the related quadratic programming (QP) on-line optimization problems must be solved at a sub-ms sampling rate. Using complexity-reduction pre-processing techniques and a primal fast gradient method (FGM) QP solver, sufficiently short computation times for ITER are reachable using a standard personal computer (PC). In this work we explore even faster finite-word-length (FWL) implementation using field-programmable gate arrays (FPGA), which would facilitate experimental testing of such control algorithms on dynamically faster medium-sized tokamaks, and compare the computational accuracy and time with the PC implementation.
ArticleNumber 112480
Author Gerkšič, Samo
Pregelj, Boštjan
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Keywords Fast gradient method
Plasma magnetic control
Quadratic programming
FPGA
Predictive control
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Snippet •A fast implementation of model predictive control is presented.•The primal fast gradient method is used for online optimization.•Finite-word-length arithmetic...
In advanced tokamak scenarios, active feedback control of unstable resistive wall modes (RWM) may be required. A RWM is an instability due to plasma kink at...
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StartPage 112480
SubjectTerms Active control
Algorithms
Control algorithms
Fast gradient method
Feedback control
Field programmable gate arrays
FPGA
Optimization
Personal computers
Plasma magnetic control
Plasma pressure
Predictive control
Quadratic programming
Tokamak devices
Title Finite-word-length FPGA implementation of model predictive control for ITER resistive wall mode control
URI https://dx.doi.org/10.1016/j.fusengdes.2021.112480
https://www.proquest.com/docview/2554645204
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