Title :
Selection of fuzzy control rules using automatic tuning of membership functions
Author :
Nishimori, Katsumi ; Hirakawa, Susumu ; Hiraga, Hirohito ; Ishihara, Naganori
Author_Institution :
Dept. of Electr. & Electron. Eng., Tottori Univ., Japan
Abstract :
Tuning of membership functions using learning procedure in a neuro-like approach has been developed to select fuzzy control rules. The tuning method is applied to simulation of driving control of a model car to run on a straight road. Simulation results bring out similar optimal trajectories of the car in both cases of 3×3 (=9 rules) and 7×7 (=49 rules) control rule types after tuning. Estimation function of errors used in the tuning of 3×3 rule type rapidly decreases to the convergent value of that used in 7×7 with increasing learning iteration
Keywords :
automobiles; fuzzy control; learning systems; neural nets; automatic tuning; driving control; fuzzy control rules; learning iteration; learning procedure; membership functions; model car; optimal trajectories; Estimation error; Fuzzy control; Gravity; Kinetic theory; Neural networks; Optimal control; Optimization methods; Production; Roads; Wheels;
Conference_Titel :
Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2125-1
DOI :
10.1109/IJCF.1994.375146
