An adaptive neural network speed controller for permanent magnet DC motor drives

Abstract

The paper presents an adaptive speed controller for permanent magnet DC motor using an artificial neural network (ANN). The development of an efficient training algorithm is one of the key problems in designing such ANN. The output error vector of the neural network is usually used in training, instead of the actual process output error. Since the desired control action is usually unknown, the output error of the ANN controller is also unknown. A simple on-line training algorithm, which enables the neural network to be trained with the actual output error of the controlled drive plant is used. The direction of the controlled plant output response is the only a priori knowledge needed. The ANN based controller is effective, robust, and results in high performance permanent magnet DC motor drives. >