Title :
Fuzzy neural network approach to control systems
Author :
Gupta, M.M. ; Knopf, G.K.
Author_Institution :
Intelligent Syst. Res. Lab., Coll. Eng., Saskatchewan Univ., Saskatoon, Sask., Canada
Abstract :
A mathematical model for an adaptive fuzzy neuron is proposed. Each neuron within a network corresponds to a fuzzy inference rule. These neurons may learn from experience via the adaptation of synaptic modifiers. The parallel structure of a fuzzy neural network controller enables complex decisions to be made in real-time. A simplified example of a neural network for controlling the steering of an automobile is used to illustrate these notions
Keywords :
adaptive control; automobiles; fuzzy set theory; inference mechanisms; learning systems; neural nets; adaptive control; adaptive fuzzy neuron; automobile; fuzzy inference rule; fuzzy set theory; mathematical model; neural network; steering control; synaptic modifiers; Biological neural networks; Control systems; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Humans; Knowledge based systems; Mathematical model; Neurons;
Conference_Titel :
Uncertainty Modeling and Analysis, 1990. Proceedings., First International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-2107-9
DOI :
10.1109/ISUMA.1990.151302
