# Simultaneous iterative learning control of mode entrainment and error field

## TL;DR

This paper introduces an iterative learning control method to diagnose and correct static error fields in mode entrainment, enabling higher rotation frequencies and improved mode stabilization in plasma control systems.

## Contribution

It presents a novel iterative learning control approach for real-time EF correction, enhancing mode entrainment and stability in plasma devices.

## Key findings

- Rapid EF correction within a few rotation periods
- Enables higher mode entrainment frequencies
- Improves rotational stabilization and mode control

## Abstract

It is shown that static error fields (EFs) can severely limit the maximum rotation frequency achievable in mode entrainment by applied rotating fields. It is also shown that the rotation non-uniformities caused by an EF can be used to diagnose and correct said EF in real time. Simulations using typical DIII-D data show that this can be achieved within a small number of mode rotation periods by an iterative learning control algorithm. In addition to rapidly correcting the EF, this gives access to high entrainment frequencies that would not be accessible otherwise, and paves the way to rotational stabilization and improved mode control.