Abstract
Intelligent control and automation is associated with expert systems; especially, when it needs to human expertise. Earlier we introduced a framework for implementation of adaptive autonomy (AA) in human-automation interaction systems, followed by a data-fusion-equipped expert system to realize that. This paper uses fuzzy sets concept to realize the AA expert system, in a real automation application. The presented adaptive autonomy fuzzy expert system (AAFES) determines the Level of Automation (LOA), adapting it to the changing Performance Shaping Factors (PSF) of automation system. The paper includes design methodology and implementation results for AAFES, and discussion on results. Results show that AAFES yields proper LOAs, even in the new contingency situations. This is caused by AAFES’s higher intelligence than the crisp (binary) one. Moreover, since AAFES deals with fuzzy linguistic PSFs, it more realistically represents the experts’ opinion.
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