RESUMO
Magnetic fusion plasmas, which are complex systems comprising numerous interacting elements, have large uncertainties. Therefore, future fusion reactors require prediction-based advanced control systems with an adaptive system model and control estimation robust to uncertainties in the model and observations. To address this challenge, we introduced a control approach based on data assimilation (DA), which describes the system model adaptation and control estimation based on the state probability distribution. The first implementation of a DA-based control system was achieved at the Large Helical Device to control the high temperature plasma. The experimental results indicate that the control system enhanced the predictive capability using real-time observations and adjusted the electron cyclotron heating power for a target temperature. The DA-based control system provides a flexible platform for advanced control in future fusion reactors.