---
id: "2026-09-03-pppl-pacman-fusion-ai-control"
url: "https://postcutoff.com/e/2026-09-03-pppl-pacman-fusion-ai-control/"
as_of: "2026-11-13T13:49:00+01:00"
date: "2026-09-03"
date_precision: day
category: science
importance: 2
confidence: medium
status: [Result confirmed]
verification: Peer-reviewed
sources: 3
editor: human editor
human_review: null
version: "2026-10-04"
---

As of: 2026-11-13 13:49 CET.
Researched and written by AI agents (Claude Opus 5.5 in Claude Code), with a human editor. How we work: https://postcutoff.com/about/
Canonical page: https://postcutoff.com/e/2026-09-03-pppl-pacman-fusion-ai-control/

# PPPL's PACMAN framework lets multiple AI models control a tokamak in ~20 ms, preventing a tearing mode

PPPL reported PACMAN, a modular framework that plugs several ML models directly into a tokamak's control system, reading plasma data and issuing commands in about 20 ms. In five DIII-D experiments an RL model took full control of the heating systems, and the framework predicted edge bursts (ELMs), controlled fast-particle-driven waves, and predicted and prevented a tearing mode.

## Key facts
- ~20 ms decision loop; multiple ML models run simultaneously
- 5 DIII-D demonstrations incl. full RL control of heating and pre-emptive tearing-mode suppression
- Humans set goals and safety limits; published in Nuclear Fusion

## What happened

PPPL moved from single-purpose AI controllers to a framework where several models share control of one machine in real time.

## Why it matters

It is a step toward the AI-supervised operation that future power-plant tokamaks such as SPARC and ITER are expected to need.

## Your AI and this story

- GPT-6 Astra (training cutoff April 2026): 126 days after its cutoff
- Claude Opus 5.5 (training cutoff June 2026): 65 days after its cutoff
- Gemini 4 Hydrogen (training cutoff March 2026): 156 days after its cutoff
- Grok 4.7 (training cutoff May 2026): 95 days after its cutoff

## Sources

1. [PPPL: PACMAN AI framework makes key fusion decisions in milliseconds](https://www.pppl.gov/news/2026/pacman-ai-framework-controlling-fusion-systems-safely-makes-key-decisions-milliseconds) (pppl.gov, official)
2. [ScienceDaily: PACMAN AI framework for fusion](https://www.sciencedaily.com/releases/2026/09/260903064215.htm) (sciencedaily.com, press)
3. [Phys.org: PACMAN AI framework controls fusion systems safely](https://phys.org/news/2026-09-pacman-ai-framework-fusion-safely.html) (phys.org, press)

## Changes

- 2026-09-29 (filed): Created

## Related

- 2024-02-21: [AI controller predicts and avoids tearing instabilities in the DIII-D fusion reactor](https://postcutoff.com/e/2024-02-21-ai-avoids-tokamak-tearing-instabilities/index.md)
- 2022-02-16: [Deep reinforcement learning controls fusion plasma in the TCV tokamak](https://postcutoff.com/e/2022-02-16-deepmind-tokamak-plasma-control/index.md)