Speakers
Description
The 76-inch isochronous cyclotron at UC Davis is being modernized for digital control and data-driven optimization. A key challenge is stabilizing the extracted proton beam current, currently done by manually adjusting Trim Coil 10 (TC10) against magnetic drifts and source fluctuations.
This work develops a digital single-input single-output (SISO) controller that automates TC10 to regulate beam current. The system combines classical PID feedback with data-driven optimization, using a genetic algorithm (GA) to adaptively tune PID gains in the cyclotron’s non-stationary environment.
We have implemented a 200 Hz data-acquisition and control pipeline with beam diagnostics, digital logging, and a Python-based control layer for autonomous operation. Current efforts focus on characterizing the beam’s response to TC10, identifying operational regimes, and validating the GA-tuned PID controller under varying machine conditions. This adaptive system forms a practical foundation for future AI-based multivariable optimization of cyclotron operation
| In which format do you inted to submit your paper? | LaTeX |
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