Global Fixed‐Time Exact Tracking for Uncertain High‐Order Nonlinear Systems With Quantized Input

Abstract

This article investigates the problem of global fixed‐time (FT) exact tracking control for high‐order nonlinear systems (HONSs) characterized by input quantization and external disturbances. Most existing approaches for handling unknown nonlinearities rely on radial basis function neural networks (RBFNNs) or fuzzy logic systems (FLS), which typically ensure only ultimately semi‐globally bounded stability. To address this limitation, an FT output tracking control strategy with prescribed performance is developed by integrating the barrier Lyapunov function (BLF) technique with an auxiliary power integrator and a bounded estimation method. The proposed scheme guarantees that the tracking error converges to zero within an FT, while ensuring the global boundedness of all closed‐loop signals and the strict satisfaction of state constraints. Moreover, the control design does not require function approximation, parameter identification, or command filtering, and effectively avoids the singularity problem. The effectiveness of the proposed method is validated through two numerical examples.