International Journal of Electrical and Computer Engineering
Vol 12, No 6: December 2022

Estimation of water momentum and propeller velocity in bow thruster model of autonomous surface vehicle using modified Kalman filter

Hendro Nurhadi (Institut Teknologi Sepuluh Nopember)
Mayga Kiki (Institut Teknologi Sepuluh Nopember)
Dieky Adzkiya (Institut Teknologi Sepuluh Nopember)
Teguh Herlambang (Universitas Nahdlatul Ulama Surabaya)



Article Info

Publish Date
01 Dec 2022

Abstract

Autonomous surface vehicle (ASV) is a vehicle in the form of an unmanned on-water surface vessel that can move automatically. As such, an automatic control system is essentially required. The bow thruster system functions as a propulsion control device in its operations. In this research, the water momentum and propeller velocity were estimated based on the dynamic bow thruster model. The estimation methods used is the Kalman filter (KF) and ensemble Kalman filter (EnKF). There are two scenarios: tunnel thruster condition and open-bladed thruster condition. The estimation results in the tunnel thruster condition showed that the root mean square error (RMSE) by the EnKF method was relatively smaller, that is, 0.7920 and 0.1352, while the estimation results in the open-bladed thruster condition showed that the RMSE by the KF method was relatively smaller, that is, 1.9957 and 2.0609.

Copyrights © 2022






Journal Info

Abbrev

IJECE

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of ...