Depth Control of Underwater Robots Using Sliding Modes and Gaussian Process Regression



: Lima Gabriel S., Bessa Wallace M., Trimpe Sebastian

: Tiago Pereira do Nascimento, Esther Luna Colombini, Alisson Vasconcelos de Brito, Luciane Terra dos Santos Garcia, Sarah Thomaz de Lima Sá, Luiz Marcos Garcia Gonçalves

: Latin American Robotics Symposium

: 2018

: Latin American Robotics Symposium

: Proceedings of the 2018 Latin American Robotics Symposium (LARS)

: Latin American Robotics Symposium

: 8

: 12

: 978-1-5386-7762-9

: 978-1-5386-7761-2

: 2639-1775

DOI: https://doi.org/10.1109/LARS/SBR/WRE.2018.00012

: https://ieeexplore.ieee.org/document/8588519


The development of accurate control systems for underwater robotic vehicles relies on the adequate compensation for hydrodynamic effects. In this work, a new robust control scheme is presented for remotely operated underwater vehicles. In order to meet both robustness and tracking requirements, sliding mode control is combined with Gaussian process regression. The convergence properties of the closed-loop signals are analytically proven. Numerical results confirm the stronger improved performance of the proposed control scheme.



Last updated on 2024-26-11 at 12:19