Adaptive practical fixed‐time tracking control for uncertain non‐strict‐feedback systems with input delay and prescribed boundary constraints

Summary This article concentrates upon the practical fixed‐time adaptive neural tracking control problem of non‐strict‐feedback nonlinear systems with input delay and prescribed boundary constraints (PBCs). A modified appropriate auxiliary system is introduced to eliminate the complex calculations appeared in the input delay. The unknown nonlinear functions exist in non‐strict‐feedback nonlinear systems, which are approximated by the radial basis function neural networks. The adaptive practical fixed‐time control strategy is developed based on a novel coordinate transformation by utilizing the backstepping algorithm. Under the proposed controller, it can be guaranteed that the tracking error satisfies the PBCs in fixed time and all the signals in the closed‐loop system are bounded. Some numerical simulations verify the effectiveness of the control approach.