DocumentCode :
1853285
Title :
Incorporation of negative rules into fuzzy inference systems
Author :
Branson, J.S. ; Lilly, J.H.
Author_Institution :
Dept. of Electr. Eng., Louisville Univ., KY, USA
Volume :
5
fYear :
1999
fDate :
1999
Firstpage :
5283
Abstract :
This paper considers the incorporation of negative examples into fuzzy inference systems (FIS). A new method of defuzzification called dot product attenuation is presented. This is a generalization of conventional defuzzification which has the ability to incorporate negative examples into the FIS´s reasoning process. The method is illustrated with an inverted pendulum controller which has a negative rule added to its rule base. The modification of the control surface due to the introduction of the negative rule is investigated. Simple control of the path of a robot in the presence of obstructions using dot product attenuation is demonstrated
Keywords :
fuzzy logic; inference mechanisms; nonlinear control systems; pendulums; FIS; defuzzification; dot product attenuation; fuzzy inference systems; inverted pendulum controller; negative examples; negative rules; Artificial neural networks; Attenuation; Fuzzy sets; Fuzzy systems; Humans; Inference mechanisms; Learning systems; Poles and zeros; Robots; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
Conference_Location :
Phoenix, AZ
ISSN :
0191-2216
Print_ISBN :
0-7803-5250-5
Type :
conf
DOI :
10.1109/CDC.1999.833394
Filename :
833394
Link To Document :
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