For a class of uncertain nonlinear systems tracking problem, the controller is designed by using dynamic surface control method and radial base function(RBF) neural network, and the controller parameters self-optimize strategy is proposed. The dynamic surface control can overcome the control of explosion in backstepping technique by introducing
a filter at each step of the recursive procedure, and the uncertainties are approximated by using RBF neural network in each subsystem. Then an optimal objective function is defined by using gradient optimization method to search a group of optimal controller in the feasible solution of the controller parameters. Finally, numerical simulation shows the feasibility of the scheme.