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

Hendro Nurhadi, Mayga Kiki, Dieky Adzkiya, Teguh Herlambang

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.

Keywords


Autonomous surface vehicle; Bow thruster; Ensemble Kalman filter; Kalman filter

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DOI: http://doi.org/10.11591/ijece.v12i6.pp5988-5997

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578