A Nonlinear Model Predictive Control for an AUV to Track and Estimate a Moving Target Using Range Measurements

Jain, RP; Alessandretti, A; Aguiar, AP ; de Sousa, JB 

ROBOT 2017: Third Iberian Robotics Conference – Volume 1, Seville, Spain, November 22-24, 2017 

ID Authenticus: P-00N-82A

DOI: 10.1007/978-3-319-70833-1_14

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.