Refinement of Control-Oriented Model via TRANSP-Based Transport Analysis to Enable Systematic Model-based Scenario Planning in EAST

The development of advanced plasma scenarios in EAST can benefit from a more systematic model-based approach to scenario planning. As originally proposed in [1], in this scenario-planning approach a plasma-response model is combined with an optimization algorithm to determine the feedforward control inputs (actuator waveforms) that are needed to achieve a desired scenario. Both plasma-state and actuator constraints are taken into account when solving the optimization problem. However, the quality of the solution of the optimization problem is highly correlated to the quality of the plasma-response model used by the optimizer to predict the behavior of the plasma. However, since all the computations are carried out off-line before the experiment, this optimization approach to scenario planning is capable of dealing with plasma-response models of arbitrary complexity. In this work, a refined plasma-response model combining the Magnetic Diffusion Equation with either empirical scalings or transport equations for the electron temperature and density is developed and used for optimal feedforward-control design in EAST. The refinement of this physics-driven model is enabled by TRANSP-based transport analysis of dedicated plasma-response characterization experiments where the equilibrium reconstruction has been constrained by measurements from the POlarimeter-INTerferometer (POINT) system.   

 

[1] Y. Ou, C. Xu, E. Schuster et al., Plasma Physics and Controlled Fusion, 50 (2008) 115001.