Implementation of EAST Fast Vertical Position Control With Neural Network-Based Estimator

被引:0
|
作者
Song, Huihui [1 ,2 ]
Shen, Biao [1 ]
Yuan, Qiping [1 ]
Zhang, Ruirui [1 ]
Wang, Yuehang [1 ]
Guo, Bihao [1 ]
Xiao, Bingjia [1 ]
机构
[1] Chinese Acad Sci, Hefei Inst Phys Sci, Inst Plasma Phys, Hefei 230031, Peoples R China
[2] Grad Univ Sci & Technol China, Sci Isl Branch, Hefei 230026, Peoples R China
关键词
Control systems; Delays; Plasmas; Position control; Servers; Computational modeling; Coils; EAST; high-speed acquisition; neural network; vertical position; PROGRESS;
D O I
10.1109/TPS.2024.3392411
中图分类号
O35 [流体力学]; O53 [等离子体物理学];
学科分类号
070204 ; 080103 ; 080704 ;
摘要
The vertical instability of the plasma is one of the main causes of large disruption. For the operation of an elongated tokamak plasma, it is necessary to control the vertical instability of the plasma effectively. This article implements a new vertical position control algorithm by using a neural network model for more accurate vertical position estimation. Meanwhile, a high-speed acquisition and fast control system is designed, which can reduce latency and provide sufficient computing resources for the neural network. Besides, the control algorithm is deployed in the new system with a separate server. Finally, the benefit of using a neural network in the new control system to control vertical position is confirmed by EAST experiments. Experimental results indicate that the neural network can accurately calculate the vertical position under different configurations, and the high-speed acquisition and fast control system reduces the response transmission delay and enhances the vertical position control.
引用
收藏
页码:1728 / 1733
页数:6
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