2026/07/25 by Xiaohua Liu, Yuehua Chen, Yanhong Chen +4
Engineering · Computer Science · #Adaptive Control of Nonlinear Systems #Control Systems and Identification #Adaptive Dynamic Programming Control
paper · doi:10.1080/00207179.2026.2704985
This paper addresses the tracking control and disturbance rejection problem for a class of uncertain random nonlinear systems via a sampled-data nonlinear extended state observer (ESO). The key novelty and contribution lie in that, different from existing results, the proposed approach applies to systems subject to large-scale random total disturbance consisting of nonlinear unmodelled dynamics, bounded noise, coloured noise, and control gain uncertainty. A sampled-data nonlinear ESO is constructed to simultaneously estimate the unmeasurable system states and the random total disturbance. On this basis, a sampled-data nonlinear ESO-based tracking controller is designed to achieve output tracking and active disturbance rejection. Moreover, the mean square practical convergence of the closed-loop systems, including that of estimation errors and tracking errors, is rigorously proved. Numerical simulations are provided to verify the effectiveness of the proposed control scheme.