Backstepping-based adaptive control of underactuated AUV subject to unknown dynamics and zero tracking errors

• Published in: Ocean engineering Vol. 302; p. 117640
• Main Authors: Zhang, Xuxi, Jiang, Kun
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.06.2024
• Subjects: Autonomous underwater vehicles; Backstepping; Neural networks; Zero-error tracking control; Autonomous underwater vehicles; Backstepping; Zero-error tracking control; Neural networks
• ISSN: 0029-8018; 1873-5258
• DOI: 10.1016/j.oceaneng.2024.117640

This paper introduces a zero-error tracking control solution for underactuated autonomous underwater vehicle (AUV) facing unknown dynamic and environmental disturbances. The proposed approach integrates the backstepping method with adaptive techniques and neural networks to effectively address the challenges posed by uncertainties and external disturbances, thereby enhancing the robustness and adaptability of AUV. Subsequently, a boundary estimation method is employed to dynamically update a single adaptive parameter online, leading to a significant reduction in computational workload. To achieve superior asymptotic tracking performance, a different coordinate transformation of fusion scalar function is designed. Moreover, a rigorous analysis of the proposed control scheme is conducted using the Lyapunov-based method, establishing that the tracking error converges asymptotically to zero. Simulation experiments are executed to illustrate the efficacy of the proposed control scheme. •An adaptive backstepping control was developed based on coordinate transformations that integrates scalar functions for underactuated AUV subject to external disturbance and unknown dynamics.•An advantage of the control scheme is that it only contains one adaptive law.•A class of underactuated dynamic models was considered, which makes the controller design more challenging to guarantee the robustness of the system.