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DOI: 10.14569/IJACSA.2020.0110982
PDF

Parameter Estimation of the ALBA Autonomous Surface Craft

Author 1: Melanie M. Valdivia-Fernandez
Author 2: Brayan A. Monroy-Ochoa
Author 3: Daniel D. Yanyachi
Author 4: Juan C. Cutipa-Luque

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 9, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Arequipa region holds the largest extension of the Peruvian littoral at the Pacific sea, has also fresh water resources composed of rivers and lagoons from the coast to the Andes highland. The ALBA vehicle is a low-cost autonomous surface vessel with open source architecture that is being developed to support water monitoring tasks in the region. This article deals with the nonlinear identification problem for an autonomous surface craft and the maximum likelihood estimation approach is used to estimate its parameters. The parametric nonlinear model is considered with simulated and experimental data. The results shows good fitting values when two, three and a maximum four parameters are estimated.

Keywords: Autonomous surface craft; parameter estimation; modeling; maximum likelihood; nonlinear; zigzag

Melanie M. Valdivia-Fernandez, Brayan A. Monroy-Ochoa, Daniel D. Yanyachi and Juan C. Cutipa-Luque, “Parameter Estimation of the ALBA Autonomous Surface Craft” International Journal of Advanced Computer Science and Applications(IJACSA), 11(9), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110982

@article{Valdivia-Fernandez2020,
title = {Parameter Estimation of the ALBA Autonomous Surface Craft},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110982},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110982},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {9},
author = {Melanie M. Valdivia-Fernandez and Brayan A. Monroy-Ochoa and Daniel D. Yanyachi and Juan C. Cutipa-Luque}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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