A Class of Uncertain System Control Via Adaptive NN Design

In this paper, an adaptive neural network control scheme is presented for a class of nonlinear systems in the strict-feedback form, together with unknown nonlinearities and unknown linear parameters. Via adopting backstepping methodology and suitably choosing the design parameters, all the signals in the closed-loop are guaranteed to be semi-globally uniformly ultimately bounded and the output of the system is proven to converge to a small neighborhood of the desired trajectory. Furthermore, we end up this work with a simulation verifying the effectiveness of the proposed approach.