Abstract

The new LHC experiments at CERN will have very large numbers of channels to operate. In order to be able to configure and monitor such large systems, a high degree of parallelism is necessary. The control system is built as a hierarchy of sub-systems distributed over several computers. A toolkit-SMI++, combining two approaches: finite state machines and rule-based programming, allows for the description of the various sub-systems as decentralized deciding entities, reacting in real-time to changes in the system, thus providing for the automation of standard procedures and for the automatic recovery from error conditions in a hierarchical fashion. In this paper we will describe the principles and features of SMI++ as well as its integration with an industrial SCADA tool for use by the LHC experiments and we will try to show that such tools, can provide a very convenient mechanism for the automation of large scale, high complexity, applications.

Highlights

  • INTRODUCTIONIn the context of Joint Controls Project (JCOP) a common architecture has been devised and a common control Framework [2] has been developed

  • LARGE Control Systems, like the ones needed by the LHC experiments have some specific requirements

  • This tree is composed of two types of nodes: “Device Units” (Devs) which are capable of “driving” the equipment to which they correspond and “Control Units” (CUs) which correspond to sub-systems and can monitor and control the sub-tree below them

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Summary

INTRODUCTION

In the context of JCOP a common architecture has been devised and a common control Framework [2] has been developed. This Framework is based on a SCADA (Supervisory Control And Data Acquisition) system called PVSSII [3]. PVSSII, providing most of the needed features, does not provide for hierarchical control and abstract behavior modeling. Another tool: SMI [4] has been integrated with PVSSII and can be used as a component of the Framework

ARCHITECTURE
FRAMEWORK
SML Language
FRAMEWORK INTEGRATION AND FEATURES
Hierarchical Control
Partitioning
Distribution
Error Handling
Automation
System Operation and Run Control
CONCLUSIONS
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