Model-free anti-disturbance tracking control for high-order discrete-time nonlinear system based on concurrent learning extended state observer

The research objective of this paper is to address the tracking control problem of high -order discretetime nonlinear systems in the presence of completely unknown internal uncertainties, unknown external disturbances, and unknown control input gain. To address this challenge, the paper proposes a high -order discrete -time model -free anti -disturbance tracking control method without relying on prior knowledge of system parameters. The core of the approach is the development of a data -driven concurrent learning extended state observer. The uniqueness of this observer lies in its ability to estimate unknown control input gains without the persistent excitation and ensure the convergence of the estimates. Based on the concurrent learning extended state observer, a high -order discrete -time tracking control law is designed to precisely track the reference signal, ensuring the stability of the nonlinear closed -loop system. The effectiveness of this method was verified by applying simulation verification to the heading tracking control of surface automatic vehicles.