Adaptive control of induction motors using Neuro-Fuzzy controllers

Abstract

This study proposes an adaptive and robust speed control for voltage based indirect vector controlled induction motors using a Proportional-Integral type Neuro-Fuzzy Controller (PI-NFC) with the inputs of speed error and error integral. Speed control performance of induction motors is affected by parameter deviations and nonlinearities in the induction motor drives. The aim of the proposed control scheme is to improve the performance and robustness of the induction motor drives under nonlinear loads and parameter variations. Furthermore, the steady-state speed error is eliminated using the proposed PI-NFC. Simulation results showing the speed control performance of the PI-NFC for the induction motor drives are presented by comparing the performance of various neuro-fuzzy control approaches under nonlinear loads and parameter variations.