Neural network based adaptive tracking of uncertain nonlinear systems in triangular form

An adaptive neural network controller is developed for a class of uncertain nonlinear systems in triangular (pure-feedback) form. The design procedure is a combination of adaptive backstepping and neural network based design techniques. It is shown that, under appropriate assumptions, the solution of the closed-loop system is uniformly ultimately bounded, and the tracking error may be made arbitrarily small by adjusting the parameters in the control law