Title :
Knowledge-based supervisory process control: applying fuzzy sets to blackboard control architecture
Author :
Fathi, M. ; Holte, K. ; Lueg, C. ; Scharnetzki, R.
Author_Institution :
Dept. of Comput. Sci., Dortmund Univ., Germany
Abstract :
The blackboard control architecture has proven to be qualified for tasks as complex as supervisory process control. The task structure framework permits a hierarchical decomposition of tasks into subtasks common in the domain of supervisory process control. Qualitative task descriptions based on fuzzy sets grant the integration of the task structure framework while preserving the inherent flexibility of the blackboard control architecture. Fuzzy sets are further qualified to improve the basic control cycle. Linguistic variables allow the specification of control knowledge in a more natural way according to human knowledge
Keywords :
blackboard architecture; fuzzy control; fuzzy set theory; intelligent control; knowledge representation; process control; blackboard control architecture; control knowledge; fuzzy sets; hierarchical task decomposition; knowledge-based supervisory process control; linguistic variables; qualitative task descriptions; specification; task structure; Computer architecture; Computer science; Control systems; Electrical equipment industry; Fuzzy sets; Industrial control; Manufacturing industries; Patient monitoring; Problem-solving; Process control;
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-7174-2
DOI :
10.1109/ANNES.1995.499462