An intelligent control architecture for accelerator beamline tuning

Authors:
William B. Klein;Carl R. Stern;George F. Luger;Eric T. Olsson
Affiliations:
Vista Control Systems, Inc., Los Alamos, NM;Vista Control Systems, Inc., Los Alamos, NM;Department of Computer Science, University of New Mexico, Albuquerque, NM;Department of Computer Science, University of New Mexico, Albuquerque, NM
Venue:
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Year:
1997

Citing 5
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Abstract

This paper discusses a new architecture for accelerator tuning that combines heuristic and knowledge based methods with traditional approaches to control. Control of particle accelerators requires a hybrid architecture, which includes methodologies for planning, intelligent search, and pattern recognition. Control is distributed and hierarchical to utilize parallel problem-solving in the face of time-sensitive control requirements and to decompose complex control problems into more manageable subtasks. For perspective, we discuss past attempts at accelerator control and why these attempts left many issues unresolved. We describe the details of our control architecture along with its motivation. We then report the results of deploying and testing it at two accelerator facilities. This paper ends with a discussion of the commercial importance of this work.