DocumentCode :
811357
Title :
Using building blocks to design analog neuro-fuzzy controllers
Author :
Vidal-Verdu, F. ; Rodriguez-Vazquez, Angel
Author_Institution :
Dept. of Electron., Malaga Univ., Spain
Volume :
15
Issue :
4
fYear :
1995
Firstpage :
49
Lastpage :
57
Abstract :
We present a parallel architecture for fuzzy controllers and a methodology for their realization as analog CMOS chips for low- and medium-precision applications. These chips can be made to learn through the adaptation of electrically controllable parameters guided by a dedicated hardware-compatible learning algorithm. Our designs emphasize simplicity at the circuit level-a prerequisite for increasing processor complexity and operation speed. Examples include a three-input, four-rule controller chip in 1.5-μm CMOS, single-poly, double-metal technology.
Keywords :
CMOS analogue integrated circuits; computational complexity; fuzzy control; fuzzy logic; inference mechanisms; learning (artificial intelligence); microcontrollers; 1.5 micron; analog CMOS chips; analog neuro-fuzzy controllers; building blocks; dedicated hardware-compatible learning algorithm; double-metal technology; electrically controllable parameters; four-rule controller chip; parallel architecture; processor complexity; CMOS technology; Circuits; Energy consumption; Fuzzy control; Fuzzy sets; Fuzzy systems; Hardware; Inference algorithms; Power system dynamics; Very large scale integration;
fLanguage :
English
Journal_Title :
Micro, IEEE
Publisher :
ieee
ISSN :
0272-1732
Type :
jour
DOI :
10.1109/40.400633
Filename :
400633
Link To Document :
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