A learning algorithm for a neural network in a linearlizer for nonlinear systems

The purpose of this study is to give a design method of a linearlizer by using a neural network (NN) with off-line learning algorithm. This linearlizer works so that the input-output property of the augmented system which consists of the system and the NN may be equivalently equal to that of the linear model. The learning of the NN is performed off-line by using the input and output data of the system. Finally, a numerical simulation is demonstrated to illustrate how to use it in the control problem.