Model predictive control of resistive wall mode for ITER

TL;DR

This paper presents an advanced model predictive control method for stabilizing resistive wall modes in ITER, demonstrating improved performance and robustness over traditional LQG control through simulation studies.

Contribution

It introduces a reduced-order MPC approach with input constraints and fast gradient optimization for RWM stabilization in ITER, enhancing control robustness and efficiency.

Findings

MPC outperforms LQG in simulation for RWM stabilization.

The control method is robust to noise and model uncertainties.

The approach effectively enlarges the domain of attraction for unstable modes.

Abstract

Active feedback stabilization of the dominant resistive wall mode (RWM) for an ITER H-mode scenario at high plasma pressure using infinite-horizon model predictive control (MPC) is presented. The MPC approach is closely-related to linear-quadratic-Gaussian (LQG) control, improving the performance in the vicinity of constraints. The control-oriented model for MPC is obtained with model reduction from a high-dimensional model produced by CarMa code. Due to the limited time for on-line optimization, a suitable MPC formulation considering only input (coil voltage) constraints is chosen, and the primal fast gradient method is used for solving the associated quadratic programming problem. The performance is evaluated in simulation in comparison to LQG control. Sensitivity to noise, robustness to changes of unstable RWM dynamics, and size of the domain of attraction of the initial conditions of the unstable modes are examined.