Abductive model refinement for accelerator control

Many aspects of accelerator control require a complex procedure that includes planning, control, and re-evaluation of the process model. As control actions are performed new information is obtained from the system which allows the model to be adjusted. In many cases, observed errors in the model suggest certain control actions for gathering new information used for further refining the model. The process of comparing predicted with observed behavior to produce testable hypotheses for adjusting the predictive model is called abductive model refinement. This paper describes our ideas for applying abductive model refinement to beamline tuning tasks, including minimum steering through a set of quadrupole lenses and developing a waist at a specified location in a beamline