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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
         
        
            Conference_Location : 
Phoenix, AZ
         
        
        
            Print_ISBN : 
0-7803-5250-5
         
        
        
            DOI : 
10.1109/CDC.1999.833394