Abstract The determination of hydrodynamic coefficients of full-scale ROV using system identification (SI) is an extremely powerful technique. The procedure is based on experimental runs and on the analysis of on-board sensors and thrusters signals. The technique is cost effective and it has high repeatability; however, it lacks accuracy due to the sensors noise and the poor modeling of thruster–hull and thruster–thruster interaction effects. In this work, forced oscillation tests using a planar motion mechanism (PMM) were undertaken with a full-scale open-frame ROV. These tests are unique in the sense that there are not many examples in the literature taking advantage of a PMM installation for testing a prototype and, consequently, allowing the comparison between the experimental results and the ones estimated by SI. The Morison equation inertia and drag coefficients were estimated with two parameter identification methods that are the weighted and the ordinary least-squares procedures. Error analysis showed that the ordinary least-squares provided better accuracy and, therefore, was used to evaluate the ratio between inertia and drag forces for a range of Keulegan–Carpenter and Reynolds numbers. The research provided a rich amount of reference data for comparison with reduced models as well as for ROV dynamic motion simulation.
[1]
M. Caccia,et al.
Modeling and identification of open-frame variable configuration unmanned underwater vehicles
,
2000,
IEEE Journal of Oceanic Engineering.
[2]
Subrata K. Chakrabarti,et al.
Handbook of Offshore Engineering
,
2005
.
[3]
Andres El-Fakdi,et al.
On the Identification of Non Linear Models of Unmanned Underwater Vehicles
,
2003
.
[4]
Julian Wolfram,et al.
On the estimation of Morison force coefficients and their predictive accuracy for very rough circular cylinders
,
1999
.
[5]
T. Sarpkaya,et al.
Mechanics of wave forces on offshore structures
,
1981
.
[6]
Minoo H. Patel.
Dynamics of Offshore Structures
,
1989
.
[7]
Louis L. Whitcomb,et al.
Advances in dynamical modeling and control of underwater robotic vehicles
,
2003
.
[8]
Louis L. Whitcomb,et al.
Adaptive identification of dynamically positioned underwater robotic vehicles
,
2003,
IEEE Trans. Control. Syst. Technol..
[9]
M. Nomoto,et al.
A deep ROV "DOLPHIN 3K": Design and performance analysis
,
1986
.