Morishita Yuya, Murakami Sadayoshi, Kenmochi Naoki, Funaba Hisamichi, Yamada Ichihiro, Mizuno Yoshinori, Nagahara Kazuki, Nuga Hideo, Seki Ryosuke, Yokoyama Masayuki, Ueno Genta, Osakabe Masaki
Department of Nuclear Engineering, Kyoto University, Kyoto, Japan.
National Institute for Fusion Science, National Institutes of Natural Sciences, Toki, Japan.
Sci Rep. 2024 Jan 17;14(1):137. doi: 10.1038/s41598-023-49432-3.
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.
磁聚变等离子体是由众多相互作用的元素组成的复杂系统,具有很大的不确定性。因此,未来的聚变反应堆需要基于预测的先进控制系统,该系统具有自适应系统模型和对模型及观测中的不确定性具有鲁棒性的控制估计。为应对这一挑战,我们引入了一种基于数据同化(DA)的控制方法,该方法基于状态概率分布描述系统模型自适应和控制估计。基于DA的控制系统首次在大型螺旋装置上实现,用于控制高温等离子体。实验结果表明,该控制系统利用实时观测提高了预测能力,并针对目标温度调整了电子回旋加热功率。基于DA的控制系统为未来聚变反应堆的先进控制提供了一个灵活的平台。