An　adaptive　neural　network　dynamic　surface　control　method　for　strict　feedback　non-linear　systems　with　model　uncertainty　is　proposed　in　this　paper.　The　uncertain　parts　are　approached　by　RBF　neural　network;　meanwhile,　the　virtual　controller　is　designed　to　make　system　stable　according　to　dynamic　surface　control.　The　method　of　Lyapunov　is　used　to　prove　the　stability　and　convergence　of　the　system.　The　simulation　results　prove　the　feasibility　of　this　controller　and　prove　that　the　controller　has　an　advantage　to　approach　the　uncertain　non-linear　system　and　make　system　have　well　convergence　and　traceability.　A　simplified　adaptive　neural　network　dynamic　surface　control　method　for　strict　feedback　non-linear　systems　with　model　uncertainty　is　proposed　in　this　paper.image