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Model-based design of multi-mode feedback control in the RFX-mod experiment

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Abstract

Interest in real-time control of magnetic field errors and magnetohydrodynamic (MHD) instabilities has been growing in the last decades due to the demanding stability requirements of high-performance scenarios in fusion devices. In this framework, the RFX-mod experiment (Sonato et al 2003 Fusion Eng. Des. 66 161) plays an important role. One of the main goals of RFX-mod is to explore high-plasma current regimes up to 2 MA for the first time in a reversed-field pinch. To this aim, RFX-mod is equipped with an advanced active coil system for the control of error fields and MHD modes, such as tearing and resistive-wall modes. As far as tearing modes are concerned, both controlling their edge radial magnetic field and maintaining them into slow (∼10–100 Hz) rotation are crucial to reduce both the plasma–wall interaction and the core magnetic stochasticity. In this paper, a model-based optimization of the RFX-mod feedback control is presented. The aim is to find an optimal gain set for a spectrum of multiple tearing modes, which produces the lowest possible value of the edge radial magnetic field, maintaining at the same time the modes into slow rotation and avoiding coil current saturations. These optimal gains have first been calculated offline by simulating the non-linear dynamics of a spectrum of tearing modes interacting through viscous and electromagnetic torques, using an adaptation to the RFX-mod multiple-shell layout of the model described in Zanca (2009 Plasma Phys. Control. Fusion 51 015006). This gain set has been obtained by scanning the proportional and derivative gains and has been tested in an extensive experimental campaign, showing good agreement with the model. With this approach, a reduction in the edge radial magnetic field up to 15%, with respect to discharges in which an empirical optimization was used, has been obtained. The above model proved to be a powerful tool to tune a multi-mode controller offline, which allowed us to save a large amount of experimental time.

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