Operators set plasma objectives while a simulator-trained policy coordinates all coils on physical hardware.
Collections: Embodied work · Negative results
Executive brief
AI can move humans up from hand-crafting every control law to specifying objectives, but only when simulation, constraints, and machine protection form a hard envelope.
AI value · Plasma current and shape tracking error
VerifiedAcross the full 0.1-1.0 second interval, RMSE was 0.62 kA for plasma current and 0.75 cm for shape.
Research-machine demonstration, not commercial fusion-power operation.
Before
Designs a controller for a predefined plasma state and configuration. → Runs the engineered controller during an experimental discharge.
After
Specifies plasma shape, current, and location objectives. → Commands all magnetic coils at high frequency to track the requested plasma configuration.
Human boundary
The policy controls coils only within the approved discharge; researchers authorize experiments, objectives, constraints, and shutdowns.
Why it matters
Operators set plasma objectives while a simulator-trained policy coordinates all coils on physical hardware.
Before
How the work ran before the change.
Control engineer
Designs a controller for a predefined plasma state and configuration.
ControlPhysics models, engineering constraints, and machine protection.
Tokamak operator
Runs the engineered controller during an experimental discharge.
ControlOperational safety limits.
What changed
Operators set plasma objectives while a simulator-trained policy coordinates all coils on physical hardware.
Decision rightAI acts within a human backstop
After
How the same work runs now.
Research operator
Specifies plasma shape, current, and location objectives.
ControlSimulator training plus physical and operational constraints.
RL controller
Commands all magnetic coils at high frequency to track the requested plasma configuration.
ControlTCV machine protection and operator-defined objectives.
Exception path
Machine-protection systems and operators terminate or override a discharge when limits are breached.
Decision authority
The policy controls coils only within the approved discharge; researchers authorize experiments, objectives, constraints, and shutdowns.
| # | Actor | Action | Control |
|---|---|---|---|
| 01 | Control engineer | Designs a controller for a predefined plasma state and configuration. | Physics models, engineering constraints, and machine protection. |
| 02 | Tokamak operator | Runs the engineered controller during an experimental discharge. | Operational safety limits. |
| # | Actor | Action | Control |
|---|---|---|---|
| 01 | Research operator | Specifies plasma shape, current, and location objectives. | Simulator training plus physical and operational constraints. |
| 02 | RL controller | Commands all magnetic coils at high frequency to track the requested plasma configuration. | TCV machine protection and operator-defined objectives. |
Work that left the path
Human role before
Engineers designed configuration-specific feedback controllers and operators executed them.
Human role after
Humans define objectives, validate policies in simulation and hardware experiments, and retain experimental and safety authority.
AI role
Decision mode: closed-loop control within a protected experiment. The learned policy sets coil commands to shape and stabilize plasma.
A novel learned controller had not previously demonstrated direct full-coil magnetic control on tokamak hardware.Across the full 0.1-1.0 second interval, RMSE was 0.62 kA for plasma current and 0.75 cm for shape.
Experimental discharges reported in 2022. · Physical TCV tokamak controlling 19 magnetic coils.
Research-machine demonstration, not commercial fusion-power operation.
Engineering-driven control of pre-designed states.The controller produced conventional, elongated, negative-triangularity, snowflake, and sustained two-droplet configurations.
Reported experimental campaign. · Multiple real-world TCV configurations.
Demonstrated configurations do not establish generalization to other tokamaks.
Anti-pattern
Treating a research demonstration as evidence of autonomous commercial fusion operation.
Questions
Portability conditions
Reputation risk
medium