Title :
Intelligent control and estimation in power electronics and drives
Author_Institution :
Dept. of Electr. Eng., Tennessee Univ., Knoxville, TN, USA
Abstract :
Intelligent control and estimation of power electronic systems by fuzzy logic and neural network techniques show tremendous promise for the future. The paper discusses primarily the work done in this area in the University of Tennessee Power Electronics Laboratory. Altogether seven projects are discussed These are: (1) fuzzy controlled DC motor drive, (2) induction motor drive with fuzzy efficiency optimizer, (3) fuzzy logic based control of wind generation system, (4) AC machine temperature and winding resistance estimation by fuzzy logic, (3) neural network based feedback signal estimation of AC drive, (6) neuro-fuzzy efficiency optimization of induction motor drive, and (7) waveform estimation by neural network
Keywords :
DC motor drives; electric machine analysis computing; electric resistance; feedback; fuzzy control; induction motor drives; intelligent control; machine control; machine windings; neural nets; parameter estimation; wind turbines; AC drive; AC machine temperature estimation; Power Electronics Laboratory; Tennessee University; fuzzy controlled DC motor drive; fuzzy efficiency optimizer; fuzzy logic; fuzzy logic based control; induction motor drive; intelligent control; intelligent estimation; neural network based feedback signal estimation; neural network techniques; neuro-fuzzy efficiency optimization; power electronics; waveform estimation; wind generation system; winding resistance estimation; Control systems; Drives; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Intelligent control; Neural networks; Power electronics; Temperature control;
Conference_Titel :
Electric Machines and Drives Conference Record, 1997. IEEE International
Conference_Location :
Milwaukee, WI
Print_ISBN :
0-7803-3946-0
DOI :
10.1109/IEMDC.1997.604201
