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A general purpose fuzzy controller for monotone functions.

C J Wu¹, A H Sung

¹Dept. of Comput. Sci., New Mexico Tech., Socorro, NM.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|January 1, 1996

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A new general-purpose fuzzy controller is introduced for monotonic functions. This controller utilizes a novel mean-of-inversion (MOI) defuzzification method, ensuring guaranteed convergence and accuracy in control systems.

Area of Science:

Control Systems Engineering
Fuzzy Logic Theory

Background:

Fuzzy controllers are widely used in control systems.
Existing defuzzification methods like mean-of-maximum (MOM) and center-of-area (COA) have limitations in certain applications.

Purpose of the Study:

To propose a general-purpose fuzzy controller for monotonic functions.
To introduce and validate the mean-of-inversion (MOI) defuzzification method for improved accuracy and convergence.

Main Methods:

Development of a general-purpose fuzzy controller architecture.
Formulation of rules for fuzzy subset selection and decision tables.
Implementation and theoretical proof of the mean-of-inversion (MOI) defuzzification method.
Comparison with traditional mean-of-maximum (MOM) and center-of-area (COA) methods.

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Main Results:

The proposed fuzzy controller effectively handles monotonic functions.
The mean-of-inversion (MOI) method demonstrates guaranteed convergence and accuracy.
MOI defuzzifies rules individually, offering a distinct advantage over superimposed methods.

Conclusions:

The proposed general-purpose fuzzy controller with MOI defuzzification offers a robust solution for monotonic functions.
The MOI method provides a theoretically sound and practically effective alternative to existing defuzzification techniques.