We present a portable system for intelligent control of particle accelerators. This system is based on a hierarchical distributed architecture. At the lowest level, a physical access layer provides an object-oriented abstraction of the target system. A series of intermediate layers implement general algorithms for control, optimization, data interpretation, and diagnosis. Decision making and planning are organized by knowledge-based components that utilize knowledge acquired from human experts to appropriately direct and configure lower level services. The general nature of the representations and algorithms at lower levels gives this architecture a high degree of potential portability. The knowledge-based decision-making and planning at higher levels gives this system an adaptive capability as well as making it readily configurable to new environments. Significant successes of this work are reported in [1,2]. DESIGNING AN ARCHITECTURETo be most useful, control architectures should be flexible enough to incorporate the important tools necessary for robust control, and should include design features which support the application of those tools in a timely and transparent manner. Our control architecture attempts to meet the following six requirements:1. The use of conventional control techniques where appropriate. Conventional control is the best solution for a large class of problems, and consists of established, well developed, robust techniques for dealing with linear and approximately linear small systems. The use of high-level control knowledge from experts in the field.More complex control systems include highlevel knowledge and information obtained through knowledge-engineering sessions with a human expert. This knowledge is preserved in the form of symbolic data sets (rules, relations, objects, etc.) and is manipulated through sophisticated, high-level reasoning mechanisms. This knowledge-based component encodes internal control information about how and when to use classes of control algorithms and heuristics and for storing configuration information for PID, neural network, fuzzy control, etc. The use of supervisory control for dealing with macro state transitions.For instance, in beam line tuning, if a failure in an upstream monitor forces the use of stripline data in judging beam intensity and distribution, a downstream controller may need to use a control algorithm which is less precise, faster, and less sensitive to intermittent failure or noise. Supervisory control can also be used for control over different internal control subsystems. Support for real time reactive control.In this case, "real time" means the ability to compute and perform "satisfactory" or "good enough" decisions that are not delayed due to control system response. The control of complex systems through the use of a hierarchical distributed architecture.To perform intelligent control that optimizes behavior in complex systems, a control architecture should support the ability to coordinate the individual partitions of the...

Pancreatic injuries in the athlete are seldom reported in the literature. These injuries can result from atraumatic etiologies and blunt abdominal trauma. Atraumatic pancreatic injuries in the athlete are diagnosed and treated in a similar manner to the nonathletic patient. Fluid replacement, analgesic support, metabolic stabilization, and minimization of gastric stimulation are the primary management methods for this type of pancreatic injury. Athletically related traumatic pancreatic injury is associated with a high morbidity and mortality. The consequences of a delayed diagnosis make this type of injury an important diagnostic consideration in an athlete with abdominal pain. Initial clinical, radiologic, and laboratory findings of direct injury to the pancreas are often equivocal, and require clinical suspicion and further investigation. Current evidence suggests that pancreatic duct injury is the primary cause of the morbidity and mortality associated with the direct trauma. A conservative or surgical management plan should be based on a combination of serial clinical examinations, pancreatic enzyme levels, and either magnetic resonance retrograde choleopancreatogram or endoscopic retrograde chloangiopancreatography investigations to rule out ductal injury. The prevention of pancreatic and other intra-abdominal injuries is an evolving area of sports medicine research. Sports specific epidemiologic data collection and analysis are important elements in the development of evidence-based interventions.

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Tuning and controlling particle accelerators is time consuming and expensive. Inherently nonlinear, the control problem is one to which conventional methods cannot satisfactorily be applied. Advanced information technologies such as expert systems and neural networks have been applied separately to the problem, with isolated success. Few, if any, of these advanced information technologies have been applied for general use or in a manner useful to multiple accelerator installations. We discuss results of coupling neural network and expert systems technology to solve several standard accelerator tuning problems based on realistic simulations. We also examine the effectiveness of additional heuristic search techniques such as genetic algorithms. Finally, we show the integration of this hybrid AI system with an existing general-purpose control system. Project OverviewThe goal of this project is to develop a very flexible, intelligent controller that can reduce the tuning time for a particle accelerator and can develop "better" tunes than are now achieved by human operators. Additionally, the intelligent controller should maintain the tune with smaller deviations than are currently exhibited. Various approaches have been taken to automate the control of accelerators [1,2,3], with varied degrees of success. Generally, most effort has been directed toward solving problems for a particular facility and little effort has been directed to developing more general solutions applicable to a number of different accelerator facilities. This paper reports the early status of this project after the first phase of the research.The architectural framework for the controller is an expert system that guides more specialized controllers based on the state of the system and the tuning goal. We developed a realistic simulation environment to test the controller operation. We have examined several types on controllers, including back propagation neural networks, fuzzy logic controller, analytic based tuning by the expert system, and genetic algorithm tuners.Steering, a standard zero-order problem, is one of the initial tasks of a beamline tuner. We first considered the basic situation in which steering was controlled by two steering magnets (SMs) separated by some distance. Two beam position monitors (BPMs) downstream of the steerers monitored the effect of the steerers. Steering must take into account beamline alignment, electronic offset and drift, and downstream tuning requirements. In general, there is jitter in the initial beam coordinates with some frequency. Beam-source mechanical and electrical variation causes this jitter, which limits steering accuracy.Another basic element of beam transport is the periodic line for focusing. Beam root mean square (rms) sizes are measured on profile monitors (PMs), which directly measure intensity distribution. These PMs, usually wire scanners, contain inherent inaccuracies due to beam fluctuation during measurement and component error. The relationship between quadrupole settings and ...

Vista Control Systems. Inc. has de~eloped a portable system for intelligent accelerator control. Our design is general in scope and is thus conf&urable to a wide range of accelerator facilities and control problems. The control system employs a multi-layer organization in which knowledge-based decision making is used to dynamically cordlgure lower level optimization and control algorithms. An object-oriented physical access layer (PAL). supported by the Vsvstem control database. allows abstraction from the lower level details of hardtvare manipulation. signai processing, and synchronization. A teleo-reactive sequencing mechanism is used to coordinate control actions. This architecture has been implemented in two deployed Wstems. one for automated accelerator tuning at the Brookhaven ATF and one for Argonne ATLAS. Several weeks of field testing at these two facilities have yielded very promising results. We describe the technical details of this architecture as well as our experiences in field testing in this report. Historicu[ overview.The goal of this project was to design and prototype a portable intelligent control system for particle accelerators. The design was required to be general and to involve the assembly of general components, in order to expedite porting of the control system to new facilities. The design was intended to support robust adaptive behavior, in order to address weakly modeled systems, and to replace the role of human operators in performing the tuning and adaptations necessary to realize system objectives in everyday operations.The initial strategy for achieving these goals was to incorporate "intelligent" and "soft computing" technologies, expert systems, fuzzy logic, neural networks, genetic algorithms, etc. The challenge was to incorporate these technologies into a principled and systematic design that combines both conventional and intelligent control methods. The design that emerged from Phase I research and that was developed in Phase 11was hierarchical, distributed, and object-oriented.