Nonlinear Burn Control of ITER’s Two-temperature Plasmas Using Optimal and Adaptive Allocation of Actuators with Uncertain Dynamics

V. Graber, E. Schuster

28th IAEA Fusion Energy Conference

Nice, France, October 12-17, 2020 -> May 10-15, 2021 (Remote)

Abstract

ITER will be the first tokamak to sustain a fusion-producing, or burning, plasma. If the plasma temperature were to inadvertently rise in this burning regime, the positive correlation between temperature and the fusion reaction rate would establish a destabi- lizing positive feedback loop. Careful regulation of the plasma’s temperature and density, or burn control, is required to prevent these potentially reactor-damaging thermal excur- sions, neutralize disturbances and improve performance. In this work, a Lyapunov-based burn controller is designed using a full zero-dimensional nonlinear model. An adaptive estimator manages destabilizing uncertainties in the plasma confinement properties and the particle recycling conditions (caused by plasma-wall interactions). The controller reg- ulates the plasma density with requests for deuterium and tritium particle injections. In ITER-like plasmas, the fusion-born alpha particles will primarily heat the plasma elec- trons, resulting in different electron and ion temperatures in the core. By considering separate response models for the electron and ion energies, the proposed controller can independently regulate the electron and ion temperatures by requesting that different amounts of auxiliary power be delivered to the electrons and ions. These two commands for a specific control effort (electron and ion heating) are sent to an optimal control allocation module that maps them to the heating actuators available to ITER: an electron cyclotron heating system (20 MW), an ion cyclotron heating system (20 MW), and two neutral beam injectors (16.5 MW each). The control allocator finds the optimal mapping by solving a convex quadratic program that includes actuator saturation and rate limits. An adaptive control allocation module is also developed as part of this work to handle uncertainties in the mapping between the commanded control efforts and the allocated actuators. This includes actuator efficiencies and the fractions of neutral beam heating that are deposited into the plasma electrons and ions. Furthermore, the adaptive allo- cator considers actuator dynamics that contain uncertainties. The adaptive allocation algorithm is formulated as a more computationally efficient dynamic update-law instead of an optimization problem. Simulation studies assess the performance of the proposed adaptive burn controller augmented with each of the optimal control allocation modules.