INTELLIGENT CONTROL
- George Luger, UNM
- William B. Klein, UNM/Vista Control Systems, Inc.
- Carl Stern, Vista Control Systems, Inc.
- Eric Olsson, UNM/Vista Control Systems, Inc.
- Mike Kroupa, Vista Control Systems, Inc.
- Bob Westervelt, Vista Control Systems, Inc.
What we are doing...
This project is a collaborative effort betweenVista Control Systems, Inc. of Los Alamos, NM and researchers at UNM. The goal of this project is to create a portable, intelligent control system that
successfully tunes the beam of a linear particle accelerator. To
accomplish this task, we have built a large scale, distributed control
system that simulates the actions of a human operator to steer, focus, and
adjust the components of an accelerator beamline. The system is organized
as a hierarchy of program elements that dynamically coordinate and delegate
control actions. These program elements, known as controllers and solvers,
incorporate knowledge-based control, genetic algorithms, neural networks,
and other techniques from artificial intelligence.
At the lowest level of the hierarchy there is a Physical Access Layer (PAL)
that abstracts the elements of a particular beamline into object models.
These abstractions allow the control system to use high level concepts to
manipulate beamline control elements. The PAL is built on an efficient
software data bus called Vsystem, developed by Vista. Abstractions in the
PAL combine Vsystem data channels into objects that encapsulate the
functionality of a typical control element, such as a magnet or monitor.
The abstraction and encapsulation of individual beamline elements allows
our system to be easily ported between different accelerator facilities.
As a high level control mechanism, we use a planning technique known as
Teleo-Reactive programming developed by Nils Nilsson at Stanford. Teleo-reactive programming
combines the responsiveness of an analog feedback loop, typical of classic
control theory, and the goal-oriented behavior of a production system, to
allow our control system to govern the execution of its tasks in a dynamic
environment. TR mechanisms enable the system to either take advantage of
felicitous events in the environment, or to appropriately fall back in its
plan to a previous state when outside events interfere with the proper
execution of a plan.
Our system remains under development, but has been successfully tested at
both the Brookhaven National Laboratory ATF and at the ATLAS facility at
Argonne National Laboratory.
PUBLICATIONS
-
Klein, W., Stern, C., Luger, G., and Olsson,
E. 1997. An Intelligent Control Architecture for
Accelerator Beamline Tuning, Proceedings of Innovative Applications
of Artificial Intelligence, Cambridge: MIT Press.
-
Klein, W., Stern, C., Luger G., and Olsson, E.
1997. Designing a Portable Architecture for Intelligent
Particle Accelerator Control, Proceedings of the Particle Accelerator
Conference, American Physical Society.
-
Klein, W., Stern, C., Kroupa, M., Westervelt,
R., Luger G., and Olsson, E. 1997. Tuning and
Optimization at Brookhaven and Argonne: Results of Recent
Experiments, Proceedings of the Particle Accelerator Conference,
American Physical Society.
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