Adaptive robust neural network control for a class of nonlinear systems using backstepping
一类非线性系统基于Backstepping的自适应鲁棒神经网络控制

The adaptive neural control scheme was formulated for a class of unknown nonlinear systems based on backstep-ping technique. The proposed scheme relaxed the requirements of matching condition and of a known bound on the network reconstruction. The method expands the applicable scope of the class of nonlinear systems, which can successfully utilize the backestepping algorithm and adaptive NN control .The resulting closed-loop system is proven to be ultimately uniform bounded, and the output tracking error converges to an adjustable neighborhood of zero.