Title :
RBF fuzzy controller with virus-evolutionary genetic algorithm
Author :
Shimojima, Koji ; Kubota, Naoyuki ; Fukuda, Toshio
Author_Institution :
Dept. of Micro Syst. Eng., Nagoya Univ., Japan
Abstract :
We propose a self-tuning fuzzy controller with virus-evolutionary genetic algorithm(VEGA). This learning algorithm is based on the virus theory of evolution. The VEGA can reduce the number of fuzzy rules by reverse transcription operator and transduction operator. The effectiveness of the proposed method is shown through some simulations of a cart-pole problem
Keywords :
feedforward neural nets; RBF fuzzy controller; cart-pole problem; fuzzy rules; reverse transcription operator; self-tuning fuzzy controller; transduction operator; virus-evolutionary genetic algorithm; Convergence; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Humans; Neural networks; Shape; Tuning;
Conference_Titel :
Neural Networks, 1996., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-3210-5
DOI :
10.1109/ICNN.1996.549041
