Energy-optimal Three-dimensional Path-following Control of Autonomous Underwater Vehicles under Ocean Currents

TL;DR

This paper introduces a 3D energy-efficient path-following control method for autonomous underwater vehicles that optimizes energy use by adjusting setpoints and employs model predictive control, outperforming conventional methods.

Contribution

It proposes a novel two-stage control architecture combining energy optimization with model predictive control for 3D underwater path following.

Findings

Achieves over 13% energy savings in simulations.

Allows non-zero relative heave velocity to improve efficiency.

Demonstrates effectiveness in different ocean current scenarios.

Abstract

This paper presents a three-dimensional (3D) energy-optimal path-following control design for autonomous underwater vehicles subject to ocean currents. The proposed approach has a two-stage control architecture consisting of the setpoint computation and the setpoint tracking. In the first stage, the surge velocity, heave velocity, and pitch angle setpoints are optimized by minimizing the required vehicle propulsion energy under currents, and the line-of-sight (LOS) guidance law is used to generate the yaw angle setpoint that ensures path following. In the second stage, two model predictive controllers are designed to control the vehicle motion in the horizontal and vertical planes by tracking the optimal setpoints. The proposed controller is compared with a conventional LOS-based control that maintains zero heave velocity relative to the current (i.e., relative heave velocity) and derives pitch angle setpoint using LOS guidance to reach the desired depth. Through simulations, we show that the proposed approach can achieve more than 13% energy saving on a lawnmower-type and an inspection mission under different ocean current conditions. The simulation results demonstrate that allowing motions with non-zero relative heave velocity improves energy efficiency in 3D path-following applications.