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Modelling of a surface vessel from free running test using low cost sensors

Wang, Y, Chai, S ORCID: 0000-0001-5186-4456 and Nguyen, HD ORCID: 0000-0003-0118-8597 2017 , 'Modelling of a surface vessel from free running test using low cost sensors', in Proceedings of the 3rd International Conference on Control, Automation and Robotics (ICCAR 2017) , Institute of Electrical and Electronics Engineers, Inc., USA, pp. 299-303 .

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Abstract

Identification of hydrodynamic coefficients and accessibility of accurate mathematical model to predict actual responses of vessels has practical significance to design computer-based simulators and apply new control algorithms, thus effective methods and proper devices should be investigated to do the modelling. The aim of this study was to estimate hydrodynamic coefficients of a surface vessel from the free running test using an experimental modelling method. Working as the embedded platform and data acquisition card, myRIO was utilized to control the scaled model, namely 'P&O Nedlloyd Hoorn', and measure her motion states using low cost sensors including a Global Positioning System (GPS) receiver, accelerometer, gyroscope and digital compass. System identification was conducted utilizing the processed experimental data with Kalman filter to estimate the hydrodynamic coefficients of a mathematical model in four degree of freedom (DOF) including surge, sway, yaw and roll. The developed mathematical model of the scaled model was validated through the comparison between the experimental data and simulation results. It has demonstrated that the proposed low cost hardware and system identification algorithm is capable of estimating hydrodynamic coefficients of the proposed mathematical model of the scaled surface vessel.

Item Type: Conference Publication
Authors/Creators:Wang, Y and Chai, S and Nguyen, HD
Keywords: myRIO, low cost sensors, free running test, signal processing, system identification
Journal or Publication Title: Proceedings of the 3rd International Conference on Control, Automation and Robotics (ICCAR 2017)
Publisher: Institute of Electrical and Electronics Engineers, Inc.
Copyright Information:

Copyright 2017 IEEE

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