Intelligent control and estimation in power electronics and drives

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.