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Abstract
Modern accelerators use multi-cell Superconducting RF cavities (SCRF) operating with very narrow resonance widths. Prior to assembly of these cavities in a cryomodule, they must be mechanically tuned to the correct frequency, either manually or with the aid of a tuning machine. The tuning process involves squeezing or stretching each cell of the cavity until the electrical frequency of the operating mode reaches a particular target frequency and the cavity is mechanically straight (low eccentricity). Currently available tuning machines require very highly skilled operators. Large scale production of such cavities by industry will require tuning machines that can be operated by semi-skilled or unskilled operators. One of the goal of the Cavity Tuning Machine (CTM) project was to minimize the intervention required by the operator by automating the tuning process to whatever extent possible.
This thesis describes the development and implementation of automated control algorithms for the tuning of SCRF cavities.
Specifically, the algorithms implemented aims to minimize the intervention required by the operator in the tuning process.
The algorithms accepts data from the tuning machine network analyzer, position encoders, and laser eccentricity monitor, process that information, and uses feed-forward and/or feedback to control the pressure applied to the tuning jaws.
After requirements and assembling detailed specifications have been collected, a survey of suitable control algorithms has been conducted. Based on the results of this survey, an algorithm to automatically control the eccentricity of the cavity during tuning has been designed. The algorithm has been implemented, integrated into the tuning machine control system and tested. Once the integration and testing has been completed, the performance of the algorithm has been measured and the results has been compared to the specifications.
