Estimation of the hydrodynamic coefficients of an autonomous underwater vehicle is the purpose of this paper. The Kalman filter method has been used for estimating the AUV hydrodynamic coefficients. To estimate hydrodynamic coefficients without knowing their initial values, spatial and temporal information of the AUV are needed. This information can be collected through different methods including experimental methods which gather the required information by the sensors installed on the AUV. In this paper, outputs related to the time and location information are collected using robot maneuver simulation in CFX software, with a movable grid being used to simulate the robot maneuver. In movable grid method, when the mesh quality has been reduced by a certain level, the meshing around the robot is summoned to the WB environment and after performing the new meshing, it is returned to the CFX environment to continue the simulation. To derive the hydrodynamic coefficients of the autonomous underwater vehicle, a sinusoidal maneuver at three degrees of freedom is selected for simulation in CFX software. The collected results from the sine maneuver simulation are applied as input to the Kalman filter estimator code. The hydrodynamic coefficients whose extraction is desired, are defined as unknown parameters in the robot control equations. In this maneuver the hydrodynamic coefficients have been extracted with good accuracy. Also to improve the Matlab code and increase the accuracy of extracting hydrodynamic coefficients, the control equation are written in the matrix form. Thus, the number of extracted coefficients are decreased but the coefficients are extracted with higher accuracy.
Lin, Z., Liao, S. “Calculation of Added Mass Coefficients of 3D Complicated Underwater Bodies by FMBEM”, Communications in Nonlinear Science and Numerical Simulation, PP. 187-194, 2011.
Ghassemi, H., Yari, E. “The Added Mass Coefficient Computation of Sphere”, Ellipsoid and Marine Propellers Using Boundary Element Method, Polish Maritime Research, Vol. 18, No. 1, pp. 17-26, 2011.
Jagadeesh, , Murali, K.” Experimental Investigation of Hydrodynamic Force Foefficients over AUV Hull form”, Journal Article Published Jan 2009 in Ocean Engineering Volume 36 issue 1 on pages 113 to 118.
Lee, S. K., Joung, T. H., Cheo, S. J., Jang, T. S. Lee, J. H. “Evaluation of the Added Mass for a Spheroid-type Unmanned Underwater Vehicle by Bertical Planar Motion Mechanism Test”, International Journal of Naval Architecture and Ocean Engineering, Vol. 3, No. 3, pp. 174-180, 2011.
CAN, M. “Numerical Simulation of Hydrodynamic Planar Motion Mechanism Test for Underwater Vehicles”, Thesis, Middle East Technical University, 2014
Ray, , Chatterjee, D. “Unsteady CFD Simulation of 3D AUV Hull at Different Angles of Attack “, Journal of Naval Architecture and Marine Engineering. December, 2016.
Li, B. “Dynamics and Control of Autonomous Underwater Vehicles with Internal Actuators”, Thesis, Florida Atlantic University, 2016.
Arani, H. A., Mahdi, M. “Numerical Analysis of Oscillation Frequency and Amplitude Effects on the AUV Hydrodynamic Derivatives in the Pure Heave Motion”, Underwater Engineering Journal Vol. 1, pp. 63-73, 2016.
Kim, H., Ranmuthugala, D., Leong, Z. Q., Chin, C. “Six-DOF Simulations of an Underwater Vehicle Undergoing Straight Line and Steady Turning Manoeuvres”, Ocean Engineering, Vol. 150, pp. 102-112, 2018.
Nouri, N. M., Mostafapour, K. “ CFD Modeling of Wing and Body of an AUV for Estimation of Hydrodynamic Coefficients“, Journal Article Published 1 Nov 2016 in Journal of Applied Fluid Mechanics volume 9 issue 6 on pages 2717 to 2729.
DU, X., ZHENG, Z. “ Numerical Calculation of Hydrodynamic Interactions of Submarine Flow on AUV”, Proceedings Article published May 2018 in 2018. OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO).
Alessandri, A., Caccia, M., Indiveri, G., Veruggio, G. “Application of LS and EKF Techniques to the Identification of Underwater Vehicles”, in Proceeding of, 1084-108.
Kim, J., Kim, K., Choi, H. S., Seong, W., Lee, K.Y. “Estimation of Hydrodynamic Coefficients for an AUV Using Nonlinear Observers”, IEEE Journal of Oceanic Engineering, Vol. 27, No. 4, pp. 830-840, 2002.
Luque, J. C., Donha, D. C. “Auv Identification and Robust Control”, in Proceeding of.
Araki, M., Sadat-Hosseini, H., Sanada, Y., Tanimoto, K., Umeda, N., Stern, F. “Estimating Maneuvering Coefficients Using System Identification Methods with Experimental, System-Based, and CFD Free-Running Trial data”, Ocean Engineering, Vol. 51, pp. 63-84, 2012.
Sabet, M. T., Sarhadi, P., Zarini, M. “Extended and Unscented Kalman Filters for Parameter Estimation of an Autonomous Underwater Vehicle”, Ocean Engineering, Vol. 91, pp. 329-339, 2014.
Sabet, M. T., Daniali, H. M., Fathi, A., Alizadeh, E. “Identification of an Autonomous Underwater Vehicle Hydrodynamic Model Using the Extended, Cubature, and Transformed Unscented Kalman filter”, IEEE Journal of Oceanic Engineering, Vol. 43, No. 2, pp. 457-467, 2018.
Sajedi, y., Bozorg, M. “Robust Estimation of Hydrodynamic Coefficients of an AUV Using Kalman and H∞ filters “, Journal Article, Ocean Engineering,pp 386 to 394, Jun 2019.
Prestero, T. T. J. “Verification of a Six-Degree if Freedom Simulation Model for the REMUS Autonomous Underwater Vehicle”, Thesis, Massachusetts Institute of Technology, 2001.-
Myring, D. “A Theoretical Study of Body Drag in Subcritical Axisymmetric Flow”, The Aeronautical Quarterly, Vol. 27, No. 3, pp. 186-194, 1976.
mahdi, M., & malekpoor, M. (2022). Extraction of Hydrodynamic Coefficients of the Remus Underwater Vehicle Robot by Coupling the CFX Software Simulator and Kalman Filter Estimator Code.. Fluid Mechanics & Aerodynamics, 11(1), 71-81.
MLA
miralam mahdi; Mohammad malekpoor. "Extraction of Hydrodynamic Coefficients of the Remus Underwater Vehicle Robot by Coupling the CFX Software Simulator and Kalman Filter Estimator Code.", Fluid Mechanics & Aerodynamics, 11, 1, 2022, 71-81.
HARVARD
mahdi, M., malekpoor, M. (2022). 'Extraction of Hydrodynamic Coefficients of the Remus Underwater Vehicle Robot by Coupling the CFX Software Simulator and Kalman Filter Estimator Code.', Fluid Mechanics & Aerodynamics, 11(1), pp. 71-81.
VANCOUVER
mahdi, M., malekpoor, M. Extraction of Hydrodynamic Coefficients of the Remus Underwater Vehicle Robot by Coupling the CFX Software Simulator and Kalman Filter Estimator Code.. Fluid Mechanics & Aerodynamics, 2022; 11(1): 71-81.
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