A method for the identification of the damping, restoring, and coupling parameters in the equations describing the coupled heave and pitch motions for an underwater robotic vehicle (URV) sailing near sea surface in random waves using only its measured responses at sea is presented. The random decrement equations are derived for the URV performing coupled heave and pitch motions in random waves. The hydrodynamic parameters in these equations are identified using a new identification technique called RDLRNNT, which uses a combination of a multiple linear regression algorithm and a neural networks technique. The combination of the classical parametric identification techniques and the neural networks technique provides robust results and does not require a large amount of computer time. The developed identification technique would be particularly useful in identifying the parameters for both moderately and lightly damped motions under the action of unknown excitations effected by a realistic sea. Numerically generated data for the coupled heave and pitch motion of a URV are used initially to test the accuracy of the technique. Experimental data are also used to validate the identification technique. It is shown that the developed technique is reliable in the identification of the parameters in the equations describing the coupled heave and pitch motions for an URV.

Issue Section:
Technical Papers
Keywords:
underwater vehicles, robots, ocean waves, motion estimation, hydrodynamics
Topics:
Algorithms, Artificial neural networks, Damping, Equations of motion, Excitation, Robotic vehicles, Seas, Waves, Vehicles, Spectral energy distribution
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