Adaptive Fuzzy Approaches to Modelling Operator Functional States in a Human-Machine Process Control System

Adaptive Fuzzy Approaches to Modelling Operator Functional States in a Human-Machine Process Control System

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...

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Hauptverfasser: Mahfouf, M., Zhang, J., Linkens, D.A., Nassef, A., Nickel, P., Hockey, G.R.J., Roberts, A.C.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Adaptive control
Fuzzy control
Fuzzy sets
Fuzzy systems
Genetic algorithms
Humans
Man machine systems
Process control
Programmable control
Psychology
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Zusammenfassung: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.
ISSN:1098-7584
DOI:10.1109/FUZZY.2007.4295371