Adaptive control of strict-feedback nonlinear systems with output constraints and input delays

In this paper, the adaptive control problem of strict-feedback nonlinear systems with output constraints and input delay is studied. By using the auxiliary system to eliminate the effect of input delay. At the same time, the unknown nonlinear functions are effectively approximated by using neural network. It is explained by the theoretical analysis that the tracking error is asymptotically converging to zero and the constructed Barrier Lyapunov function (BLF) can ensure that the requirement of system output is not violated. Finally, simulation results are given to illustrate the effectiveness of the method.