An adaptive backstepping nonlinear controller based RBF neural network

This paper proposes an adaptive RBF neural network based Backstepping nonlinear controller (ANNBC) for a class of nonlinear systems with some uncertain parameters. The proposed ANNBC gives a design approach to drive the nonlinear system tracking a setting course. For the adaptive laws of the controller are derived in the sense of Lyapunov function and Barbalat's Lemma, the stability can be guaranteed. Finally, the nonlinear ship steering system is used as an example to test the controller, and the simulation shows that the proposed ANNBC can achieve better tracking performance.