Intelligent control of a cryogenic cooling plant based on blackboard system architecture

Intelligent system techniques have been rapidly assimilating into process c ontrol engineering, with many applications reported in the last decade. Int elligent control is bringing a new perspective as well as new challenges to process control. In this paper, a software architecture for a Blackboard f or Integrated Intelligent Control Systems (BIICS) is described. The system is designed to simultaneously support multiple heterogeneous intelligent me thodologies, such as neural networks, expert systems, fuzzy logic, neural n etworks and genetic algorithms. It will be shown how such methodologies can be readily assimilated into the software architecture. The BIICS system re presents a multi-purpose platform for design and simulation of intelligent control paradigms for different kinds of processes. Currently the system ut ilizes intelligent control techniques (neuro-fuzzy and genetic optimization ) for controlling a cryogenic plant used for superconductor testing at temp eratures below 100 K. (C) 2000 Elsevier Science Ltd. All rights reserved.