A comparison of neural network control algorithms

Abstract

This paper presents a comparison of three common neural network controllers: model predictive control, NARMA-L2 control and model reference control. We describe each of the controllers and demonstrate their performance on four applications: a continuous stirred tank reactor, a robot arm, a magnetic levitation system and a simple diesel engine model. The strengths and weaknesses of each algorithm are illustrated.