Robust backstepping control of nonlinear systems in discrete-time using multilayer neural networks

A multilayer neural network (NN) controller for the robust back stepping control of nonlinear systems in discrete-time is presented. Control action is employed to achieve tracking performance for unknown nonlinear systems. Tuning methods are derived for the multilayer NN based on the delta rule. Uniform ultimate boundedness of the tracking error and the weight estimates' are presented without using the PE condition. No learning phase is needed for the NN and initialization of the network weights is straightforward.