Interval type-2 fuzzy logic systems: theory and design

We present the theory and design of interval type-2 fuzzy logic systems (FLSs). We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs: one that is based on a general inference formula for them. We introduce the concept of upper and lowe...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2000-10, Vol.8 (5), p.535-550
Main Authors: Qilian Liang, Mendel, J.M.
Format: Article
Language:English
Subjects:
Additive noise
Control systems
Design engineering
Design methodology
Engines
Fuzzy logic
Fuzzy sets
Fuzzy systems
Gaussian
Inference
Intervals
Mathematical analysis
Noise
Signal processing
Signal to noise ratio
Training data
Uncertainty
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Summary:We present the theory and design of interval type-2 fuzzy logic systems (FLSs). We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs: one that is based on a general inference formula for them. We introduce the concept of upper and lower membership functions (MFs) and illustrate our efficient inference method for the case of Gaussian primary MFs. We also propose a method for designing an interval type-2 FLS in which we tune its parameters. Finally, we design type-2 FLSs to perform time-series forecasting when a nonstationary time-series is corrupted by additive noise where SNR is uncertain and demonstrate an improved performance over type-1 FLSs.
ISSN:1063-6706
1941-0034
DOI:10.1109/91.873577