摘要

This paper focuses on the adaptive tracking control problem for a class of nonlinear non-strict-feedback systems. By introducing a compact set, the restrictive assumption that the lower bounds of the control gain functions must be positive constants is canceled in the proposed method, and the compact set is proved to be invariant set eventually. The functions in non-strict-feedback system are no longer required to be differentiable, and the neural networks are constructively used to deal with the unknown system functions, which contain the whole state variables of the non-strict-feedback system. Furthermore, it is rigorously proved that all the closed-loop signals are bounded and the tracking error converges to a small residual set asymptotically. Finally, simulation examples are provided to demonstrate the effectiveness of the designed method.