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