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1PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Dan Boyer for the Integrated Scenarios science group Plasma.

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Presentation on theme: "1PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Dan Boyer for the Integrated Scenarios science group Plasma."— Presentation transcript:

1 1PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Dan Boyer for the Integrated Scenarios science group Plasma control algorithm development on NSTX-U using TRANSP NSTX-U Program Advisory Committee Meeting (PAC-37) January 26, 2016

2 2PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 NSTX-U Mission Elements 5 Highest Research Priorities Explore unique ST parameter regimes to advance predictive capability - for ITER and beyond 1.Understand confinement and stability at high beta and low collisionality 2.Study energetic particle physics prototypical of burning plasmas Develop solutions for PMI challenge 3.Dissipate high edge heat loads using expanded magnetic fields + radiation 4.Compare performance of solid vs. liquid metal plasma facing components Advance ST as possible FNSF / Pilot Plant 5.Form and sustain plasma current without transformer for steady-state ST

3 3PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 TRANSP routinely used in interpretive mode, increasingly in predictive mode Interpretive TRANSP Injected power Equilibrium n e, T e profiles, Z eff Transport parameters Predictive TRANSP Injected power Coil currents or desired boundary Transport model T e, n e profiles, Z eff

4 4PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 High-fidelity control simulations needed for model-based control design and validation Control design typically relies on reduced modeling to make the design problem easier –Simplified analytical or empirical expression used to capture dominant phenomena –Linearization, time-scale separation, or other means are often used to further simplify the model used for design When tested experimentally, the nonlinearities and coupling of the actual system may degrade performance –Dedicated experimental time needed for commissioning Testing controllers using the integrated modeling code TRANSP prior to implementation may: –Improve controller performance and reduce time for commissioning and fine tuning –Enable demonstration of new control techniques to justify implementation and experimental time Testing Design Actual system First-principles model Simplified model (empirical/analytical scalings) Simplified model (empirical/analytical scalings) Model for control design Control design TRANSP

5 5PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 NSTX-U TRANSP feedback control simulations based on scenario development MHD equilibrium ISOLVER Heating/curre nt drive NUBEAM Sauter Transport T i : Chang- Hinton T e : prescribed n e : prescribed n i : based on Z eff Z eff : prescribed Injected power Desired boundary n e, T e profiles, Z eff S. Gerhardt, NF 2012

6 6PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Now using TRANSP as a virtual tokamak for control design MHD equilibrium ISOLVER Heating/curre nt drive NUBEAM Sauter Transport T i : Chang- Hinton T e : prescribed n e : prescribed n i : based on Z eff Z eff : prescribed Injected power Desired boundary n e, T e profiles, Z eff 1.Electron temperature and density no longer a priori inputs 2.Ability to change actuators in `real-time’, i.e., based on feedback control 3.An analog to the plasma control system (PCS) H 98, H ST f GW

7 7PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Now using TRANSP as a virtual tokamak for control design MHD equilibrium ISOLVER Heating/curre nt drive NUBEAM Sauter Transport T i : Chang- Hinton T e : prescribed n e : prescribed n i : based on Z eff Z eff : prescribed Injected power Desired boundary n e, T e profiles, Z eff 1.Electron temperature and density no longer a priori inputs 2.Ability to change actuators in `TRANSP real-time’, i.e., based on feedback control 3.An analog to the plasma control system (PCS)

8 8PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Now using TRANSP as a virtual tokamak for control design MHD equilibrium ISOLVER Heating/curre nt drive NUBEAM Sauter Transport T i : Chang- Hinton T e : prescribed n e : prescribed n i : based on Z eff Z eff : prescribed Injected power Desired boundary n e, T e profiles, Z eff 1.Electron temperature and density no longer a priori inputs 2.Ability to change actuators in `real-time’, i.e., based on feedback control 3.An analog to the plasma control system (PCS) PCS

9 9PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Ability to change actuators in `TRANSP real-time’, i.e., based on feedback control Density Plasma current Plasma boundary NTV torque Toroidal field Heating/CD Confinement factor Physics layer Engineering layer Hardware layer Implemented Implementing Not yet implemented

10 10PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Ability to change actuators in `TRANSP real-time’, i.e., based on feedback control NBI power Density Plasma current Plasma boundary NTV torque Gas puff PF coil currents OH coil current RWM coil currents Toroidal field Heating/CD Confinement factor RF sources Pellets OH coil voltage PF coil voltages Physics layer Engineering layer Hardware layer TF current TF voltage RWM coil voltages Implemented Implementing Not yet implemented

11 11PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Ability to change actuators in `TRANSP real-time’, i.e., based on feedback control NBI power Density Plasma current Plasma boundary NTV torque Gas puff PF coil currents OH coil current RWM coil currents Toroidal field Heating/CD Confinement factor RF sources Pellets OH coil voltage PF coil voltages Physics layer Engineering layer Hardware layer TF current TF voltage NBI modulation RWM coil voltages RWM power supplies TF power supplies PF power supplies Implemented Implementing Not yet implemented

12 12PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Several on-going projects using TRANSP feedback control framework Stored energy and q 0 control on NSTX-U –M. D. Boyer, PPPL, Experiment: XP-1509 Stored energy, q 0, and I p control on NSTX-U (non-inductive scenarios) –M. D. Boyer, PPPL, Experiment: future XP, possibly XP-1507 Rotation profile control on NSTX-U –I. Goumiri, Princeton U., Experiment: XP-1564 Current profile control on NSTX-U –Z. Ilhan, Lehigh U., Experiment: part of XP-1532 Rotation profile control on DIII-D –W. Wehner, Lehigh U. Shape control on NSTX-U –M. D. Boyer, PPPL NTM control on ITER –F. Poli, PPPL

13 13PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Several on-going projects using TRANSP feedback control framework Stored energy and q 0 control on NSTX-U –M. D. Boyer, PPPL, Experiment: XP-1509 Stored energy, q 0, and I p control on NSTX-U (non-inductive scenarios) –M. D. Boyer, PPPL, Experiment: future XP, possibly XP-1507 Rotation profile control on NSTX-U –I. Goumiri, Princeton U., Experiment: XP-1564 Current profile control on NSTX-U –Z. Ilhan, Lehigh U., Experiment: part of XP-1532 Rotation profile control on DIII-D –W. Wehner, Lehigh U. Shape control on NSTX-U –M. D. Boyer, PPPL NTM control on ITER –F. Poli, PPPL

14 14PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Several on-going projects using TRANSP feedback control framework Stored energy and q 0 control on NSTX-U –M. D. Boyer, PPPL, Experiment: XP-1509 Stored energy, q 0, and I p control on NSTX-U (non-inductive scenarios) –M. D. Boyer, PPPL, Experiment: future XP, possibly XP-1507 Rotation profile control on NSTX-U –I. Goumiri, Princeton U., Experiment: XP-1564 Current profile control on NSTX-U –Z. Ilhan, Lehigh U., Experiment: part of XP-1532 Rotation profile control on DIII-D –W. Wehner, Lehigh U. Shape control on NSTX-U –M. D. Boyer, PPPL NTM control on ITER –F. Poli, PPPL

15 15PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Using TRANSP to test q 0 and β N control via beam power and outer gap size actuation Small outer gap Large outer gap Boundary can have strong effect on q profile through –Effect on beam deposition profile –Effect on bootstrap current through change in elongation Two reference boundaries with different outer gap sizes were chosen, and interpolated between based on the feedback controller request M.D. Boyer, NF 2015

16 16PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 State-space system identification used for designing simultaneous q 0 and β N controller Open loop signals applied to each actuator in several TRANSP runs Linear dynamic model optimized to predict outputs

17 17PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Optimal controller achieves good target tracking in TRANSP simulations Evolution tracks step change in requested values Controller increases outer gap and decreases beam power to track change in request Controller has important implications for MHD stability – ability to avoid q=1, or to move radius of the q=2 surface to avoid 2/1 NTMs.

18 18PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Several on-going projects using TRANSP feedback control framework Stored energy and q 0 control on NSTX-U –M. D. Boyer, PPPL, Experiment: XP-1509 Stored energy, q 0, and I p control on NSTX-U (non-inductive scenarios) –M. D. Boyer, PPPL, Experiment: future XP, possibly XP-1507 Rotation profile control on NSTX-U –I. Goumiri, Princeton U., Experiment: XP-1564 Current profile control on NSTX-U –Z. Ilhan, Lehigh U., Experiment: part of XP-1532 Rotation profile control on DIII-D –W. Wehner, Lehigh U. Shape control on NSTX-U –M. D. Boyer, PPPL NTM control on ITER –F. Poli, PPPL

19 19PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 β N and q 0 control with beam line 1 and outer gap improves response and tracks targets Reference Closed loop Target Power reduced for first β N target, increased for second Outer gap decreased to speed q 0 response, increased to maintain elevated target Plasma current (not controlled) response varies from reference q 0 approaches 1 after target change (could adjust target trajectories or control gains)

20 20PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Several on-going projects using TRANSP feedback control framework Stored energy and q 0 control on NSTX-U –M. D. Boyer, PPPL, Experiment: XP-1509 Stored energy, q 0, and I p control on NSTX-U (non-inductive scenarios) –M. D. Boyer, PPPL, Experiment: future XP, possibly XP-1507 Rotation profile control on NSTX-U –I. Goumiri, Princeton U., Experiment: XP-1564 Current profile control on NSTX-U –Z. Ilhan, Lehigh U., Experiment: part of XP-1532 Rotation profile control on DIII-D –W. Wehner, Lehigh U. Shape control on NSTX-U –M. D. Boyer, PPPL NTM control on ITER –F. Poli, PPPL

21 21PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Simplified model used for rotation profile control design in NSTX-U [I. Goumiri] Using simplified form of toroidal momentum equation for design, profiles derived from TRANSP Rotation

22 22PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Simplified model used for rotation profile control design in NSTX-U [I. Goumiri] Using simplified form of toroidal momentum equation for design, profiles derived from TRANSP Rotation

23 23PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Simplified model used for rotation profile control design in NSTX-U [I. Goumiri] Using simplified form of toroidal momentum equation for design, profiles derived from TRANSP New NBI (central torque) 3D Field Coil (edge torque) Rotation

24 24PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 State-space controller achieves good tracking in TRANSP simulations [I. Goumiri] Rotation (rad/s) Beam Power (MW) Coil current [A] Coil current Time (s) Energy (MJ) Time (s) Beam power Stored energy Rotation First target Second target First target Second target Beam 1 Beam 2A Beam 2B Beam 2C

25 25PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Several on-going projects using TRANSP feedback control framework Stored energy and q 0 control on NSTX-U –M. D. Boyer, PPPL, Experiment: XP-1509 Stored energy, q 0, and I p control on NSTX-U (non-inductive scenarios) –M. D. Boyer, PPPL, Experiment: future XP, possibly XP-1507 Rotation profile control on NSTX-U –I. Goumiri, Princeton U., Experiment: XP-1564 Current profile control on NSTX-U –Z. Ilhan, Lehigh U., Experiment: part of XP-1532 Rotation profile control on DIII-D –W. Wehner, Lehigh U. Shape control on NSTX-U –M. D. Boyer, PPPL NTM control on ITER –F. Poli, PPPL

26 26PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Simplified current profile model used for feedback and feedforward control design Magnetic diffusion equation –Similar form to momentum diffusion equation –Enables similar modeling approach Multiple actuators considered: –Loop voltage –Individual beam heating –Density Feedback controller for tracking and disturbance rejection designed and tested in TRANSP Feedforward control optimization based on reduced model Z. Ilhan, W. Wehner, E. Schuster

27 27PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Feedforward actuator trajectory optimization to match target q profile Optimizing for target matching Optimizing for stationarity Optimizing for both Time (s) Z. Ilhan, W. Wehner, E. Schuster

28 28PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Complexity of the control requirements for NSTX-U motivates use of model-based control A TRANSP framework for testing feedback controllers prior to experiments has been developed: –Generate and test control-oriented models –Test/tune feedback control algorithms –Test new algorithms, demonstrate new control approaches Future work –Test on NSTX-U! Summary and future work

29 29PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Backup Slides

30 30PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Real-time measurements Actuators Performance requirements Dynamics By incorporating dynamic models in the design process, control algorithms can be made to handle all of these issues Feedback control of NSTX-U is a complex task but model-based design can help Nonlinearities Coupling Multiple actuators Spatially distributed Actuator limitations Competing goals Constraints (MHD stability) Limited Noisy Control design problem

31 31PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Modifications have been implemented using external code: the Expert file Expert subroutine called at many places throughout TRANSP production code An identifier is passed along with the call –different snippets of code can be run at different points during the simulation Custom run-specific code can be run at each call to manipulate certain variables (which would typically be input ahead of time) based on the state of the simulation

32 32PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Profiles and coil currents during optimal controller simulation 7s: change in outer gap shifts q 0 up Less peaked NBCD Increased bootstrap cur. Coil currents appear physically achievable

33 33PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Reference simulation w/ fixed OH current: slow response, sensitivity to disturbances NB sources: 1B, 1C, 2A, and 2B Outer gap: 14cm Broad n e, T e profiles from NSTX 142301 Particle inventory held fixed during simulation Slow evolution to 100% non-inductive –Can feedback control speed up response or track different targets? Perturbations in density, confinement, and profile shapes can affect response –Can feedback recover performance? Reference Perturbed density q 0 < 1 earlier with lower density

34 34PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Beam line 1 power increased to track reference β N Increasing beam power and β N leads to increased current –Reference current nearly recovered despite no feedback control on current Outer gap adjusted to maintain q 0 β N and q 0 feedback using beam line 1 and outer gap control during confinement pert. Reference Perturbed Closed loop

35 35PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Left: β N control w/ beam line 1 Right: q 0 control w/ outer gap Reference Closed loop Target q 0 drops below 1 since it is not controlled Targets tracked in both cases Target tracking

36 36PAC-37, Plasma control algorithm development on NSTX-U using TRANSP, M.D. Boyer, 1/26/2016 Feedforward actuatory trajectory optimization

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