Remarks on the tracking method of neural network weight change for a learning-type neural network feed-forward feed-back controller

Abstract

Although many neural network controllers have been proposed, we still have to tune several parameters of neural networks in order to obtain a better learning performance in practical applications. Our tracking method provides a new aspect of this tuning of neural network parameters. It has been applied to adaptive and learning-type neural network direct controllers, and an adaptive-type neural network feed-forward feed-back controller. This work applied it to a learning-type neural network feed-forward feed-back controller. Simulation results confirmed its usefulness, and we discuss a transformation of the track on a 2D plane to one-dimensional values.