A new continuous t-norm and its application in fuzzy control

In conventional fuzzy control, MAX and MIN operators are usually adopted, but MIN and MAX operations only consider the extreme elements and ignore the contributions of other elements, which will inevitably affect the control performance. To solve this problem, we presented a new kind of t-norm and t...

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Bibliographic Details
Published inProceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393) Vol. 3; pp. 1795 - 1798 vol.3
Main Authors Dan Chen, Huacan He, Yuqin Ji, Hui Wang
Format Conference Proceeding
LanguageEnglish
Published IEEE 2000
Subjects
Application software
Boundary conditions
Computer science
Fuzzy control
Fuzzy sets
Fuzzy systems
Genetic algorithms
Logic
Optimization methods
Testing
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Summary:In conventional fuzzy control, MAX and MIN operators are usually adopted, but MIN and MAX operations only consider the extreme elements and ignore the contributions of other elements, which will inevitably affect the control performance. To solve this problem, we presented a new kind of t-norm and t-conorm, which can vary through Lukasiewicz operators, probability operators, and Zadeh operators with a correlation coefficient h ranging from [-1, 1]. On this basis we present simplified AND and OR operators to replace MAX and MIN operators in fuzzy control. In the simulation we use genetic algorithms to optimize the correlation coefficients and the simulation result shows that our method is better than the conventional one.
ISBN:078035995X
9780780359956
DOI:10.1109/WCICA.2000.862783