This paper presents a new learning algorithm for the design of Mamdani- type or fully-linguistic fuzzy controllers based on available input-output data. It relies on the use of a previously introduced parametrized defuzzification strategy. The learning scheme is supported by an investigated property of the defuzzification method. In addition, the algorithm is tested by considering a typical non-linear function that has been adopted in a number of published research articles. The test stresses on data-fitting, function shape representation, noise insensitivity and generalization capability. The results are compared with those obtained using neuro-fuzzy and other fuzzy system design approaches.
@article{urn:eudml:doc:39196,
title = {A defuzzification based new algorithm for the design of Mamdani-type fuzzy controllers},
journal = {Mathware and Soft Computing},
volume = {7},
year = {2000},
pages = {159-173},
zbl = {0992.68181},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:39196}
}
Saade, Jean Jamil. A defuzzification based new algorithm for the design of Mamdani-type fuzzy controllers. Mathware and Soft Computing, Tome 7 (2000) pp. 159-173. http://gdmltest.u-ga.fr/item/urn:eudml:doc:39196/