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A major challenge in tokamak fusion research is first-wall erosion caused by steady heat loads and sudden energy bursts known as edge-localized modes. Divertor detachment reduces steady-state heat flux, while resonant magnetic perturbations can suppress these instabilities. However, integrating the two has been difficult because they require conflicting operating conditions. Here we demonstrate simultaneous achievement of resonant magnetic perturbations mitigated small edge-localized modes and impurity seeded partial divertor detachment in plasmas with an ITER-similar shape on the DIII-D tokamak. Experiments and simulations show that resonant magnetic perturbations facilitate detachment by redistributing particles, lowering the core density and increasing the scrape-off layer density, thereby reducing the amount of injected gas required. Cooling-gas injection eliminates the secondary heat-flux peak created by three-dimensional magnetic lobes, while edge cooling weakens the plasma response to the applied magnetic fields. These advances illustrate a viable pathway for integrating edge stability control with power exhaust in future fusion reactors.

Control of the density profile based on pellet fueling for the ITER nuclear fusion tokamak involves a multi-rate nonlinear system with safety-critical constraints, input delays, and discrete actuators with parametric uncertainty. To address this challenging problem, we propose a multi-stage MPC (msMPC) approach to handle uncertainty in the presence of mixed-integer inputs. While the scenario tree of msMPC accounts for uncertainty, it also adds complexity to an already computationally intensive mixed-integer MPC (MI-MPC) problem. To achieve real-time density profile controller with discrete pellets and uncertainty handling, we systematically reduce the problem complexity by (1) reducing the identified prediction model size through dynamic mode decomposition with control, (2) applying principal component analysis to reduce the number of scenarios needed to capture the parametric uncertainty in msMPC, and (3) utilizing the penalty term homotopy for MPC (PTH-MPC) algorithm to reduce the computational burden caused by the presence of mixed-integer inputs. We compare the performance and safety of the msMPC strategy against a nominal MI-MPC in plant simulations, demonstrating the first predictive density control strategy with uncertainty handling, viable for real-time pellet fueling in ITER.