Title :
Neural network implementation of a fuzzy logic controller
Author :
Buja, Giuseppe S.
Author_Institution :
Inst. of Manage. & Eng., Padova Univ., Italy
Abstract :
Fuzzy logic is an attractive technique for plant control but suffers from complex data processing. A solution to this problem is here presented and consists in implementing a fuzzy logic controller (FLC) on a neural network (NN). As an example, a DC drive is considered. After designing a FLC for controlling the drive speed, a NN is trained by supervision to learn the input-output relationship of the FLC. It is found that a NN with few neurons implements the relationship very well. Equipment is then set up to test the NN control. The experimental responses obtained from the drive demonstrate the effectiveness of the solution
Keywords :
DC motors; digital control; electric drives; fuzzy control; learning (artificial intelligence); machine control; neural nets; velocity control; DC drive; complex data processing; drive speed; fuzzy logic controller; input-output relationship; neural network implementation; plant control; supervised learning; Artificial neural networks; Choppers; Clamps; Control systems; Engineering management; Fuzzy logic; Fuzzy reasoning; Neural networks; Senior members; Testing;
Conference_Titel :
Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on
Conference_Location :
Maui, HI
Print_ISBN :
0-7803-0891-3
DOI :
10.1109/IECON.1993.339042