Main Content

mam2sug

(To be removed) Transform Mamdani fuzzy inference system into Sugeno fuzzy inference system

mam2sug will be removed in a future release. Use convertToSugeno instead. For more information, see Compatibility Considerations.

Description

example

sugFIS = mam2sug(mamFIS) transforms a Mamdani fuzzy inference system into a Sugeno fuzzy inference system.

Examples

collapse all

Load a Mamdani fuzzy inference system.

mam_fismat = readfis('mam22.fis');

Convert this system to a Sugeno fuzzy inference system.

sug_fismat = mam2sug(mam_fismat);

Plot the output surfaces for both fuzzy systems.

subplot(2,2,1)
gensurf(mam_fismat)
title('Mamdani system (Output 1)')
subplot(2,2,2)
gensurf(sug_fismat)
title('Sugeno system (Output 1)')
subplot(2,2,3)
gensurf(mam_fismat,gensurfOptions('OutputIndex',2))
title('Mamdani system (Output 2)')
subplot(2,2,4)
gensurf(sug_fismat,gensurfOptions('OutputIndex',2))
title('Sugeno system (Output 2)')

The output surfaces for both systems are similar.

Input Arguments

collapse all

Mamdani fuzzy inference system, specified as a structure. Construct mamFIS at the command line or using the Fuzzy Logic Designer. For more information, see Build Fuzzy Systems at the Command Line and Build Fuzzy Systems Using Fuzzy Logic Designer.

Output Arguments

collapse all

Sugeno fuzzy inference system, returned as a structure. sugFIS:

  • Has constant output membership functions, whose values correspond to the centroids of the output membership functions in mamFIS

  • Uses the weighted-average defuzzification method

  • Uses the product implication method

  • Uses the sum aggregation method

The remaining properties of sugFIS, including the input membership functions and rule definitions remain unchanged from mamFIS.

Tips

  • If you have a functioning Mamdani fuzzy inference system, consider using mam2sug to convert to a more computationally efficient Sugeno structure to improve performance.

  • If sugFIS has a single output variable and you have appropriate measured input/output training data, you can tune the membership function parameters of sugFIS using anfis.

Version History

Introduced before R2006a

expand all