Artificial neural network based controller for permanent magnet DC motor drives

Abstract

This paper introduces a novel approach of designing a controller using a multi-layer feed-forward neural network (FFNN) for the speed control of a permanent magnet (PM) DC motor. The artificial neural network (ANN) controller with its massive parallel properties and learning capabilities offers a promising way to solving the problem of system nonlinearity, parameter variations and unexpected load excursions associated with a PM DC motor drive system. The self-tuning technique of the controller in real time is achieved through an improved on-line back-propagation training algorithm based on an output error propagation. The proposed ANN controller is implemented with a PM DC motor drive system in the laboratory. The laboratory test results validate the efficacy of the based controller for a high performance PM DC motor drive.