@InProceedings{10.1007/978-3-319-70833-1_14,
author="Jain, R. Praveen
and Alessandretti, Andrea
and Aguiar, A. Pedro
and de Sousa, Jo{\~a}o Borges",
editor="Ollero, Anibal
and Sanfeliu, Alberto
and Montano, Luis
and Lau, Nuno
and Cardeira, Carlos",
title="A Nonlinear Model Predictive Control for an AUV to Track and Estimate a Moving Target Using Range Measurements",
booktitle="ROBOT 2017: Third Iberian Robotics Conference",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="161--170",
abstract="In this paper, we propose a Nonlinear Model Predictive Control (NMPC) approach that is employed by an Autonomous Underwater Vehicle (AUV) to track and estimate a moving target using range measurements. Due to the nonlinearities in the observation model associated with range-only measurements, there exist state and input trajectories of the AUV that makes the position of the target unobservable. To address this problem, a standard stabilizing NMPC based approach augmented with an economic cost function is utilized to steer the system through highly observable trajectories in order to guarantee a good estimate of the position of the target. The efficacy of the proposed solution is demonstrated through simulations.",
isbn="978-3-319-70833-1"
}