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

• Type: Article in International Conference Proceedings Book
• Date: 2017

Authors

Jain, RP (Author) Other; Alessandretti, A (Author) Other; Aguiar, AP (Author) FEUP; de Sousa, JB (Author) Other

Conference proceedings International

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

Pages: 161-170

Indexing

Scopus - 4 Citations

Other information

Authenticus ID: P-00N-82A

DOI: 10.1007/978-3-319-70833-1_14

Abstract (EN): 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. © Springer International Publishing AG 2018.

Language: English

Type (Professor's evaluation): Scientific