Receding-horizon optimal control of the current profile evolution during the ramp-up phase of a tokamak discharge

Ou, Yongsheng; Xu, Chao; Schuster, Eugenio; Ferron, J. R.; Luce, T. C.; Walker, M.L.; Humphreys, D.A.

doi:10.1016/j.conengprac.2010.08.006

Cited by 35 publications

(23 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach can handle quite complicated constraints without being trapped by local minima. A reduced-order model is obtained in [24] by using the proper orthogonal decomposition (POD) method [26], which can reduce the computational burden of the extremum seeking approach in [18] and make receding horizon control a feasible approach for online implementation [17]. In [25], the open-loop optimal control problem of the q-profile is solved in ramp-up tokamak plasmas using the minimal-surface theory.…”

Section: Magnetohydrodynamic Equilibrmentioning

confidence: 99%

Dynamic optimization of trajectory for ramp‐up current profile in tokamak plasma

Ren

2016

Asia-Pacific J Chem Eng

View full text Add to dashboard Cite

In this paper, we consider an open-loop, finite-time, optimal control problem of attaining a specific desired current profile during the ramp-up phase by finding the best open-loop actuator input trajectories. Average density, total power, and plasma current are used as control actuators to manipulate the profile shape in tokamak plasmas. Based on the control parameterization method, we propose a numerical solution procedure directly to solve the original PDE-constrained optimization problem using gradient-based optimization techniques such as sequential quadratic programming (SQP). This paper is aimed at proposing an effective framework for the solution of PDE-constrained optimization problem in tokamak plasmas. A more user-friendly and efficient graphical user interface (GUI) is designed in MATLAB and the numerical simulation results are verified to demonstrate its applicability. In addition, the proposed framework of combining existing PDE and numerical optimization solvers to solve PDEconstrained optimization problem has the prospective to target challenge advanced control problems arising in more general chemical engineering processes.

show abstract

Section: Magnetohydrodynamic Equilibrmentioning

confidence: 99%

Dynamic optimization of trajectory for ramp‐up current profile in tokamak plasma

Ren

2016

Asia-Pacific J Chem Eng

View full text Add to dashboard Cite

show abstract

“…One considers the simplified poloidal magneticflux transport model (11). Let * ( , ), * ( ), and * ( , ) denote the optimal state, control, and costate variables that minimize the cost functional (10). Then the optimality conditions are given as follows:…”

Section: Optimal Open-loop Controlmentioning

confidence: 99%

“…For the online implementation, we need to attenuate external perturbations and uncertainties. Therefore, feedback control is needed for the online implementation to guarantee that the system can track the preoptimized trajectories robustly as close as possible [10][11][12]. Thus, by defining a derivation dynamic system, we can formulate a feedback control problem of the derivation system which is governed by a linear parabolic PDE system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Tracking for a Divergent-Type Parabolic PDE System in Current Profile Control

Jiang

Ren

et al. 2014

Abstract and Applied Analysis

Self Cite

View full text Add to dashboard Cite

We consider the optimal tracking problem for a divergent-type parabolic PDE system, which can be used to model the spatial-temporal evolution of the magnetic diffusion process in a tokamak plasma. With the feedforward trajectories generated by numerical optimization, we derive a linear system to describe the error evolution. The weak variation approach is then extended to cylindrical coordinates to obtain a Riccati-type PDE for feedback kernel synthesis. Then, a finite difference method is used to give numerical solutions for the Riccati-type PDE. The obtained feedback kernel is finally used to simulate the closed-loop system. The simulation results demonstrate that the proposed tracking method can attenuate the tracking error effectively.

show abstract

“…where t is the time, ψ is the poloidal magnetic flux, η is the plasma resistivity, T e is the plasma electron temperature, µ 0 = 4π × 10 −7 H/m is the vacuum permeability, j N I is the non-inductive source of current density, B is the toroidal magnetic field and − denotes flux-surface average, F, G, H are geometric factors, which are functions of ρ [12]. The proposed closed-loop receding-horizon scheme shows potential for implementation in long-discharge tokamaks such as ITER.…”

Section: Introductionmentioning

confidence: 99%

Tokamak Design as One Sustainable System

Rastovic¹

2011

NNW

View full text Add to dashboard Cite

Nowadays, remote sensing technology is being used as an essential tool for monitoring and detecting oil spills to take precautions and to prevent the damages to the marine environment. As an important branch of remote sensing, satellite based synthetic aperture radar imagery (SAR) is the most effective way to accomplish these tasks. Since a marine surface with oil spill seems as a dark object because of much lower backscattered energy, the main problem is to recognize and differentiate the dark objects of oil spills from others to be formed by oceanographic and atmospheric conditions. In this study, Radarsat-1 images covering Lebanese coasts were employed for oil spill detection. For this purpose, a powerful classifier, Artificial Neural Network Multilayer Perceptron (ANN MLP) was used. As the original contribution of the paper, the network was trained by a novel heuristic optimization algorithm known as Artificial Bee Colony (ABC) method besides the conventional Backpropagation (BP) and Levenberg-Marquardt (LM) learning algorithms. A comparison and evaluation of different network training algorithms regarding reliability of detection and robustness show that for this problem best result is achieved with the Artificial Bee Colony algorithm (ABC).

show abstract

Receding-horizon optimal control of the current profile evolution during the ramp-up phase of a tokamak discharge

Cited by 35 publications

References 33 publications

Dynamic optimization of trajectory for ramp‐up current profile in tokamak plasma

Dynamic optimization of trajectory for ramp‐up current profile in tokamak plasma

Optimal Tracking for a Divergent-Type Parabolic PDE System in Current Profile Control

Tokamak Design as One Sustainable System

Contact Info

Product

Resources

About