Extraction of Hydrodynamic Coefficients of the Remus Underwater Vehicle Robot by Coupling the CFX Software Simulator and Kalman Filter Estimator Code.

Document Type : Original Article

Authors

Department of Mechanical Engineering Shahid Rajaee Teacher Training University

Abstract

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.

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  • Receive Date: 12 February 2022
  • Revise Date: 05 July 2022
  • Accept Date: 04 August 2022
  • Publish Date: 21 September 2022