An extended fuzzy logic system for uncertainty modelling

Authors:
Jiangtao Cao;Ping Li;Honghai Liu
Affiliations:
School of Automation, Northeastern Polytechnical University, China;School of Information and Control Engineering, Liaoning Shihua University, China;Institute of Industrial Research, University of Portsmouth, UK
Venue:
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Year:
2009

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Abstract

An extended fuzzy logic system (EFLS) based on interval fuzzy membership functions is proposed for covering more uncertainty in practical applications. With the degree of uncertainty in fuzzy membership functions, interval fuzzy membership functions are self-generated to include uncertainties which occur from understanding linguistic knowledge and fuzzy rules in fuzzy methods. A novel adaptive strategy is designed to self-tune the interval fuzzy membership functions and to deduce the crisp outputs with feedback structure. An inverse kinematics modelling study based on a two-joint robotic arm has demonstrated that proposed EFLS outperforms conventional fuzzy methods.