Adaptive fuzzy approaches to modelling operator functional states in a human-machine process control system

M. Mahfouf, J. Zhang, D. A. Linkens, A. Nassef, P. Nickel, G. R.J. Hockey, A. C. Roberts

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

This paper assesses the operator functional state (OFS) of human operators based on a collection of psychophysiological and performance measures. Two types of adaptive fuzzy models, namely ANFIS (adaptive-network-based fuzzy inference system) and GA (genetic algorithm) based Mamdani fuzzy model, are employed to estimate the OFSs under a set of simulated process control tasks involved in an automation-enhanced cabin air management system (aCAMS). The adaptive fuzzy modelling procedures are described and then validated using real-life data measured from such a simulated human-machine process control system.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Fuzzy Systems, FUZZY
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Conference on Fuzzy Systems, FUZZY - London, United Kingdom
Duration: 23 Jul 200726 Jul 2007

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2007 IEEE International Conference on Fuzzy Systems, FUZZY
Country/TerritoryUnited Kingdom
CityLondon
Period23/07/0726/07/07

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