This paper investigates the problem of energy-optimal control for autonomous underwater vehicles (AUVs). To improve the endurance of AUVs, we propose a novel energy-optimal control scheme based on the economic model predictive control (MPC) framework. We first formulate a cost function that computes the energy spent for vehicle operation over a finite-time prediction horizon. Then, to account for the energy consumption beyond the prediction horizon, a terminal cost that approximates the energy to reach the goal (energy-to-go) is incorporated into the MPC cost function.
@article{arxiv.1906.08719,
title = {Energy Management for Autonomous Underwater Vehicles Using Economic Model Predictive Control},
author = {Niankai Yang and Dongsik Chang and Mohammad Reza Amini and Matthew Johnson-Roberson and Jing Sun},
journal= {arXiv preprint arXiv:1906.08719},
year = {2019}
}
Comments
6 pages, 10 figures, 2 tables, 2019 Annual American Control Conference (ACC), July 10-12, 2019, Philadelphia, PA, USA