A Bottom-Following Preview Controller for Autonomous Underwater Vehicles

This paper describes a solution to the problem of bottom-following for autonomous underwater vehicles (AUVs) that relies on the evaluation of the terrain characteristics ahead of the vehicle using echo sounders. The methodology used poses the problem as a discrete time path following control problem where a conveniently defined error state space model of the plant is augmented with bathymetric (i.e., depth) preview data. A piecewise affine parameter-dependent model representation is adopted that describes the AUV linearized error dynamics for a predefined set of operating regions. For each region, a state feedback
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control problem for affine parameter-dependent systems is posed and solved using linear matrix inequalities (LMIs). The resulting nonlinear controller is implemented as a gain-scheduled controller using the D-methodology. Simulation results obtained with a nonlinear dynamic model of the INFANTE AUV in the vertical plane are presented and discussed.