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Dynamic optimization of tokamak plasmas via control parameterization and the time-scaling transformation

机译:通过控制参数化和时标变换动态优化托卡马克等离子体

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Fusion nuclear reactions, in which multiple atomic nuclei collide to form a single atomic nucleus, can only occur at extremely high temperatures, where all matter is in the plasma state. In the majority of today's experimental fusion reactors, the fusion plasma is confined to a torus shape using a magnetic confinement system called a tokamak. The performance of a tokamak depends crucially on the current spatial profile, which is related to the poloidal magnetic flux. Accordingly, in this paper, we investigate a finite-time optimal control problem in which the aim is to drive the current spatial profile to within close proximity of a desired target profile, subject to a parabolic PDE governing the evolution of the poloidal magnetic flux. To solve this optimal control problem, we first use the finite element method to approximate the PDE model by an ODE model. Then, we apply the control parameterization and time-scaling techniques to obtain an approximate finite-dimensional optimization problem, which can be solved using sequential quadratic programming methods. Simulation results using experimental data from the DIII-D tokamak in San Diego, California demonstrate the effectiveness of the proposed approach.
机译:聚变核反应只能在极高的温度下发生,其中所有原子都处于等离子体状态,在该反应中,多个原子核碰撞形成一个原子核。在当今的大多数实验聚变反应堆中,使用称为托卡马克的磁性限制系统将聚变等离子体限制为环形。托卡马克的性能主要取决于当前的空间分布,这与极向磁通有关。因此,在本文中,我们研究了一个有限时间最优控制问题,其目的是在控制抛物线形偏微分方程控制极向磁通量演变的情况下,将当前空间轮廓驱动到所需目标轮廓的附近。为了解决这个最优控制问题,我们首先使用有限元方法通过ODE模型来近似PDE模型。然后,我们应用控制参数化和时间缩放技术来获得近似的有限维优化问题,可以使用顺序二次编程方法解决该问题。使用来自加利福尼亚圣地亚哥的DIII-D托卡马克的实验数据进行的仿真结果证明了该方法的有效性。

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