A comparison of hydrodynamic damping models using least-squares and adaptive identifier methods for autonomous underwater vehicles

This work provides a comparison of eight different hydrodynamic damping models for streamlined tail-controlled autonomous underwater vehicles (AUVs). We use an off-line least-squares method and an adaptive identifier method to approximate damping model coefficients and determine if one damping model is preferred over other models. We evaluate the two methods for estimating the parameters of the models. Our initial results show that both identification methods produce similar results, and thus the adaptive identifier might be preferred for some applications because it does not require angular acceleration. Our results also show that the linear damping model has comparable performance to more complex models but employs fewer parameters. We conclude that the linear damping model is preferred over other models due to its simplicity.