Abstract

A blackboard for integrated intelligent control systems (BIICS) software architecture has been developed. The system is designed to simultaneously support multiple heterogeneous intelligent paradigms, such as neural networks, expert systems, fuzzy logic and genetic algorithms. It is shown how such paradigms are assimilated into the software architecture. This paper describes the BIICS system as it utilises intelligent control techniques (neuro-fuzzy and genetic optimisation) for controlling a cryogenic plant used for superconductor testing by cooling the test samples to temperatures below 100 K.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.