The difficulty associated with a control design for nonaffine control systems is that an explicit inverting control
design is not possible even if the inverse exists by using the implicit function theorem. Therefore, a robust adaptive control
design method is proposed for a class of uncertain block nonaffine systems via incorporating dynamic feedback, backstepping
design, neural network, and feedback linearization techniques, in which the NNs are used to approximate and adaptively
cancel the unknown functions. The whole closed-loop system is proved to be stable in the sense of Lyapunov. Finally,
simulation results show the effectiveness of the proposed scheme.