This paper proposes the development of a model following autopilot system for an Autonomous Underwater Vehicle (AUV) depth changing control. The parameters to command a maneuver are generated off-line and selected as appropriate by the vehicle’s autonomous control system. A series of such preprogrammed maneuvers can be stored in an on-board computer, and used as command generation systems for the autopilot. The paper presents a linear model following control (LMFC) design based on the open-loop linearized vehicle model as the reference model, a robustness analysis of the scheme and simulation results of response in the diveplane using the full nonlinear vehicle system equations. LMFC has been proposed for aircraft where certain desirable handling characteristics based on an arbitrary model are required or where decoupled control for Control Configured Vehicle (CCV) performance is needed. It is shown here that this model-based LMFC autopilot for underwater vehicles exhibits relatively robust behavior under conditions of parameter uncertainty and non-linearity which is not worse than the equivalent LQR/LTR for linear output feedback systems. Also, a tailored transient response is provided, conducive to near time optimal response.
A Model Based Self Diagnosis System for Autonomous Underwater Vehicles using Artificial Neural Networks
