Comparative experimental evaluation of a new adaptive identifier for underwater vehicles

This paper reports a novel adaptive identifier for underwater vehicles as well as its local stability proof and comparative experimental evaluation. The adaptive identification algorithm estimates the hydrodynamic mass, quadratic drag, gravitational force, and buoyancy parameters of a second-order rigid-body plant under the influence of actuator forces and torques. Adaptive model identification methods do not require instrumentation of vehicle acceleration as required of other standard methods, such as conventional least squares. Previous adaptive model identification methods have focused on model-based adaptive tracking controllers however these approaches are not applicable when the plant is either uncontrolled, under open-loop control, or using any control law other than a specific adaptive tracking controller; the adaptive identifier reported herein does not require reference trajectory-tracking, and thus is applicable in these commonly occurring cases. An experimental comparison of adaptive identification and conventional least squares parameter identification is reported. The adaptively identified model is shown to be similar to the least squares identified model.