Plasma Control Solutions
Real-time plasma control solutions — combining physics-based modeling, conventional controllers, machine learning and reinforcement learning, and proven experience at operating tokamaks.
Plasma Control Challenge
Plasma is an inherently unstable, high-dimensional, and rapidly evolving system. Controlling it in real time — across the full discharge lifecycle, from initiation through flat-top and ramp-down — demands controllers that are fast, robust, and deeply integrated with the physics of the device.
Next-generation fusion devices must operate at higher performance, with tighter constraints on plasma shape, position, and stability, while maintaining strict interface contracts with safety and supervisory systems. Compounding this, available diagnostic power on these devices will be limited — reducing the number and quality of real-time measurements, and placing even greater demands on control systems to remain robust under partial observability.
Next-generation tokamaks and future fusion power plants (FPPs) require industrial-grade plasma control solutions that build on the proven conventional control experience accumulated at today's research devices — and extend it with modern approaches capable of managing the full complexity of a commercial plant: digital twin integration, multi-objective optimization across energy, stability, and operational goals, and adaptive control that can evolve with the machine over its lifetime.
Solutions
We combine physics insight, modern machine learning, and real-device deployment experience to build control systems that work in practice — not just in simulation. From controllers development and testing environment to development of custom plasma control system for your device.
Discharge scenario development
We develop and optimize discharge scenarios tailored to the physics and operational goals of your device — covering initiation, ramp-up, flat-top, and ramp-down phases, and taking into account actuator limits, stability boundaries, and control objectives.
API for controllers development
A software environment for rapid development, integration, and hardware-in-the-loop testing of plasma controllers — providing standardized interfaces to device models, actuator simulators, and real-time diagnostic streams so new controllers can be validated before live deployment.
Reinforcement learning framework
An end-to-end framework for training, evaluating, and deploying RL-based plasma controllers — including simulation environments, reward shaping for physics constraints, and transfer pipelines for moving trained policies to real PCS hardware. Demonstrated live at DIII-D.
Custom controllers development
We design and deliver controllers tailored to the specific requirements of your device and plasma control system — from shape and position control to supervisory state machines — with full support through integration, commissioning, and live operation.
Case Studies
From reconstruction-free RL controllers running live at DIII-D to formal interface contracts for AI in high-stakes physical systems — our work spans the full plasma control stack.
Reconstruction-free magnetic control of DIII-D plasma with deep reinforcement learning
Poster ↗Design and implementation of a reinforcement learning-based plasma shape controller at DIII-D
Paper ↗Robustness by design: Interface contracts for AI control in high-stakes physical systems
Poster ↗Developing a state-oriented plasma control system
See the publications page to learn more about our research and work.
Building a New Fusion Device?
Plasma control is most effective when developed alongside simulations and diagnostics — we offer all three. Talk to us.
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