Bulletin of the American Physical Society
60th Annual Meeting of the APS Division of Plasma Physics
Volume 63, Number 11
Monday–Friday, November 5–9, 2018; Portland, Oregon
Session NP11: Poster Session V: Laser-plasma Particle Acceleration; HEDP; Turbulence and Transport; DIII-D Tokamak; Machine Learning, Data Science (9:30am-12:30pm)
Wednesday, November 7, 2018
OCC
Room: Exhibit Hall A1&A
Abstract ID: BAPS.2018.DPP.NP11.121
Abstract: NP11.00121 : Real-time Optimization of the q Profile Under Constraints for Avoidance of MHD Instability and Achievement of Stationary Conditions*
Presenter:
W.P. Wehner
(Lehigh U)
Authors:
W.P. Wehner
(Lehigh U)
E. Schuster
(Lehigh U)
J.R. Ferron
(GA)
C.T. Holcomb
(LLNL)
D.A. Humphreys
(GA)
A.W. Hyatt
(GA)
K.E. Thome
(GA)
B.S. Victor
(LLNL)
A novel q profile control approach and recent DIII-D experimental results aimed at reaching stationary plasmas characterized by a flat loop voltage profile are presented. The control approach combines feedforward and feedback control commands. Both command components are computed via numerical optimal control techniques. The key advantage of the numerical computation approach is that it allows explicit incorporation of state and input constraints to prevent the controller from driving the plasma outside of stability limits and obtain, as closely as possible, stationary conditions characterized by a flat loop voltage profile. Using a suitable control-oriented model, the simulated plasma evolution in response to the actuators is embedded into a nonlinear optimization problem that provides a feedforward control policy (set of actuator waveforms) that under ideal conditions guides the plasma evolution to the desired state. The feedback controller computes updates to the feedforward control law to account for variability in plasma conditions; optimizing in real-time the plasma response to the available actuator set over a finite horizon (number of future control time-steps) while satisfying input and state constraints.
*Supported by the US DOE under DE-SC0010661 and DE-FC02-04ER54698.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DPP.NP11.121
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