Formation Tracking Control of AUVs Subject to Disturbances via Distributed Adaptive Sliding Model Predictive Control

• Published in: IEEE transactions on vehicular technology Vol. 74; no. 7; pp. 10067 - 10080
• Main Authors: Wang, Zhaoyang, Diao, Weiqing, Li, Weihao, Xu, Bo
• Format: Journal Article
• Language: English
• Published: IEEE 01.07.2025
• Subjects: Adaptation models; Adaptive sliding model; autonomous underwater vehicle; distributed model predictive control; extended state observer; Force; formation tracking control; Numerical stability; Predictive control; Predictive models; Robustness; Topology; Uncertainty; Vectors; Vehicle dynamics
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2025.3543287

Autonomous underwater vehicles (AUVs) operating in dynamic ocean environments suffer from significant challenges due to model uncertainties and external disturbances, arising from factors such as hydrodynamic variability, sensor noise, and environmental forces. With this in mind, this paper designs a robust formation tracking control scheme that incorporates a distributed adaptive sliding mode predictive controller (DASMPC). Specifically, an auxiliary stabilizable control law based on adaptive sliding mode surface (ASMC) and extended state observer (ESO) is first designed. Considering that the traditional ESO-ASMC approach has a slow convergence rate and unsatisfied stability characteristics, a rolling time horizon optimization technique is incorporated, and the new ESO-DASMPC control scheme is designed, which greatly improves the stability and the convergence of the formation system while inheriting the robustness of the existing auxiliary controller. The recursive feasibility and stability of the ESO-DASMPC algorithm are guaranteed by constructing the constraints of the auxiliary controller and associated Lyapunov function. Finally, numerical experiments studies are conducted and the simulation results validate the superiority of control performance and the robustness of the proposed scheme.