Radial basis functions neural network of vary learning rate based stochastic U-model

In this paper, an adaptive tracking control algorithm and its step by step implementation procedure are developed for a class of nonlinear plants within a U-model framework with unknown parameters. A new technique is proposed to design an online control algorithm using the Radial Basis Functions Neural Network (RBFNN).