Identification of the hydrodynamic model of an underwater robotic vehicle heaving and pitching near the sea surface using its measured response

An accurate estimation of the hydrodynamic parameters for Underwater Robotic Vehicles (URV) is a top priority for the designing of the control strategies for such vehicles. The identification of these parameters constitutes a main difficulty in the development of a URV. Several methods have been developed to estimate such parameters. These methods include: strip theory, slender body theory, semi-empirical approaches, and parametric identification. Most of these methods have many assumptions and drawbacks that restrict their applicability. -- I am mainly concerned with the parametric identification. One of the advantages of parametric identification is that if it can be done in real time then one can have a tool for updating the dynamic model as the vehicle moves through the water. Responses obtained using this model will be realistic and increase the chances of having better control of the vehicle. -- In this dissertation, I develop a new robust technique for the identification of the damping, restoring, and coupling parameters in the equations describing the coupled heave and pitch motions for an URV sailing near the water surface in random waves. The developed technique is called RDLRNNT, which is a combination of the random decrement technique, multi-linear regression algorithm, and a neural networks technique. RDLRNNT requires only the measured coupled heave rand pitch responses for the URV in random waves and does not require a prior knowledge of the wave excitation. The developed technique would be particularly useful in identifying the parameters for both moderately and lightly damped motions under the action of unknown wave excitations affected by a realistic sea. -- Numerically generated data for the coupled heave and pitch motion of an URV are used initially to test the accuracy of the technique for both different levels of damping and a wide range of damped natural frequencies in heave and pitch motions. Moreover, several case studies are further investigated to test the dependency of the developed technique on the wave excitation forms. Two different excitations are investigated: a wide-band and a narrow-band form. -- Experimental data are also used to validate the identification technique for different functions of wave excitations and different towing speeds. Three main experimental variables are further investigated: the significant wave height (Hs), the wave modal frequency (Ω), and the towing speed (U)