Software architecture for intelligent control of a cryogenic cooling plant

Intelligent system techniques have been rapidly assimilating into process control engineering, with many applications reported in the last decade. Intelligent control is bringing a new perspective as well as new challenges to process control. In this paper, a software architecture for a Blackboard for Integrated Intelligent Control Systems (BIICS) is described. The system is designed to simultaneously support multiple heterogeneous intelligent methodologies, such as neural networks, expert systems, fuzzy logic and genetic algorithms. It will be shown how such methodologies can be assimilated into the software architecture. The BIICS system (currently utilising the intelligent control techniques of neuro-fuzzy and genetic optimisation) has been applied for controlling a cryogenic plant used for superconductor testing at temperatures below 100 degrees K.