An Intelligent Control Architecture for Accelerator Beamline Tuning

William B. Klein, Carl R. Stern, George F. Luger, Eric T. Olsson

Our research in intelligent control systems has led to the design of a unique software architecture that combines heuristic and knowledge-based methods with traditional approaches to control. Emulation of the complex procedures used by human experts in controlling particle accelerators requires a hybrid architecture integrating methodologies for planning, intelligent search, and pattern recognition, among others. This system is distributed and hierarchical to utilize parallel problem-solving in the face of time sensitive control applications and to decompose complex control problems into more manageable subtasks. We use an object-oriented abstraction layer and a component-based architecture for high portability.

This paper discusses issues involved in controlling complex processes and how the problems encountered in building a general purpose control system have led to this novel design. First, the problem domain: Particle accelerator tuning, is described. To provide perspective, we discuss past attempts at accelerator control and why these attempts have left many outstanding issues. We then describe the details of this architecture along with its motivation and report the results of deploying and testing our architecture at two accelerator facilities. This paper ends with a discussion of the commercial importance of this work.

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