Paper Info
Title
Prediction-Based Seabed Terrain Following Control for an Underwater Vehicle-Manipulator System
Abstract
This article addresses a problem of seabed terrain following control (STFC) for an underwater vehicle-manipulator system (UVMS). The motivation is to perform a visual search of marine products closely to seabed in unknown environment. In terms of this issue, we propose a novel and robust STFC framework for our UVMS to maintain an appropriate height to seabed. A nonlinear model predictive control (NMPC) method is formulated to solve the STFC problem. To relieve online computational burden and system noisy influence, Ohtsuka's continuation/generalized minimal residual (C/GMRES) algorithm incorporated with a tracking differentiator (TD) is investigated. In order to improve the following accuracy, the system state prediction part of the NMPC and a long short-term memory (LSTM) network are elaborated to predict future seabed terrain using a depth gauge and an altimeter, respectively. Finally, the three different physical scenarios for STFC problem are established using ROS to demonstrate the robustness and efficiency of the proposed algorithm.
Year
DOI
Venue
2021
10.1109/TSMC.2019.2944651
IEEE Transactions on Systems, Man, and Cybernetics: Systems
Keywords
DocType
Volume
Seabed terrain following control (STFC) for underwater vehicle-manipulator system (UVMS),seabed terrain prediction,underwater vehicle control,UVMS
Journal
51
Issue
ISSN
Citations 
8
2168-2216
0
PageRank 
References 
Authors
0.34
6
6
Name
Order
Citations
PageRank
Mingxue Cai131.77
Yu Wang2399.08
Shuo Wang328451.13
Rui Wang411122.06
Long Cheng5149273.97
Min Tan62342201.12