Distributed Control of Coupled Inhomogeneous Diffusion in Tokamak Plasmas

Mavkov, Bojan; Witrant, Emmanuel; Prieur, Christophe

doi:10.1109/tcst.2017.2768039

Cited by 13 publications

(14 citation statements)

References 35 publications

(60 reference statements)

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“…This software environment allows to develop profile controllers in representative simulations (both on a local computer and in the TCV control system) and afterwards test them in experiments without changing the controller code itself. The software environment is used to prepare and test in parallel, next to the model-based predictive controller discussed here, also an adaptive controller [2], a Lyapunov-based controller [7] and a passivity-based controller (see [5] for initial results of this controller using the framework reported here), confirming the validity of the controller preparation and testing approach.…”

Section: Introductionmentioning

confidence: 55%

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

et al. 2017

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The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

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Section: Introductionmentioning

confidence: 55%

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

et al. 2017

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“…A first order Taylor series expansion around the equilibrium h = h and A s = A s is carried out. A similar approach was done for another diffusive system in [17]. As previously stated, the aim of this paper is to find A s .…”

Section: Linearized Dynamicsmentioning

confidence: 90%

The Initialization Of Basal Sliding Coefficients For Antarctica A Lyapunov Based Approach

Mourad

Witrant

Pattyn

2018

2018 Annual American Control Conference (ACC)

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Abstract-Models describing natural phenomena can depend on parameters that cannot be directly measured, hence the necessity to develop inverse techniques to determine them. The goal of this paper is to utilize such a technique to enable better initialization of ice sheet models for Antarctica. This will enable models to produce better forecasts as part of climate studies. The parameter of interest is the basal sliding coefficient, which characterizes the contact of the ice sheet with the bed underneath. A Lyapunov based approach is proposed to control the convergence of the 1D inhomogeneous transport model toward a feasible equilibrium matching the measurements. This method results in a new update law for the coefficient inversion. The results, which show an improved convergence toward the observed ice thickness, are compared with a currently used inverse method.

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“…whereH(x) is defined in (8)-(9) by only taking the h i elements in (8) and set the f i elements to 0.…”

Section: A Stability Of the Open-loop Systemmentioning

confidence: 99%

“…While some previous works emphasized on the coupling between the dynamics and used a linearized model as in [8] and the experimental validation in [9], we are interested in the nonlinearity of the dynamics. In this tokamak control perspective, control of nonlinear PDEs is a recent and challenging topic.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear PDE-Based control of the electron temperature in H-mode tokamak plasmas

Mameche

Witrant

Prieur

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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This paper studies the exponential stability of the electron temperature profile in H-mode tokamak plasmas. Lyapunov stability analysis is carried in an infinite-dimensional setting on the nonlinear partial differential equation describing the dynamics. The nonlinear components are handled with the sum of squares framework, in order to prove the exponential convergence of the Lyapunov function. Nominal stability of the system is first checked, then a controller is proposed to improve the convergence rate of the closed-loop system. The controller algorithm including the input constraints is then used for profile tracking on the RAPTOR simulator with different challenging scenarios.

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Distributed Control of Coupled Inhomogeneous Diffusion in Tokamak Plasmas

Cited by 13 publications

References 35 publications

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

The Initialization Of Basal Sliding Coefficients For Antarctica A Lyapunov Based Approach

Nonlinear PDE-Based control of the electron temperature in H-mode tokamak plasmas

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