Ananda, Mirdha Suci (2021) Implementasi Ensemble Kalman Filter Dan Regresi Linier Untuk Mendapatkan Koefisien Hidrodinamika Kapal I-Boat. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 06111740000007-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
06111740000007-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2023. Download (3MB) | Request a copy |
Abstract
Merancang model matematika gerak kapal dengan akurat sangat penting untuk kelancaran operasi kapal di perairan. Model matematika gerak kapal dapat dimanfaatkan dalam merancang aplikasi kontrol dan untuk menggambarkan kemampuan manuver kapal. Salah satu komponen pada model matematika gerak kapal adalah koefisien hidrodinamika kapal. Koefisien hidrodinamika kapal merupakan sekumpulan parameter model yang bila teridentifikasi dengan akurat mengakibatkan model tersebut mampu mengestimasi gerakan kapal dengan baik. Menentukan koefisien hidrodinamika kapal dapat dilakukan dengan identifikasi sistem berdasarkan data hasil percobaan kapal. Pada penelitian ini bertujuaan mengestimasi koefisien hidrodinamika kapal i-Boat 6 DOF. Identifikasi sistem dilakukan dengan menggunakan data percobaan i-Boat yang dilengkapi dengan IMU dan GPS. Metode Ensemble Kalman Filter digunakan dalam mengestimasi model. Kemudian hasil dari EnKF tersebut digunakan sebagai inputan dalam metode Regresi Linier untuk memperoleh nilai koefisien hidrodinamika kapal. Hasil penelitian ini menunjukkan bahwa nilai koefisien hidrodinamika yang diperoleh dapat digunakan dalam model matematika gerak i-Boat. Hal ini terlihat dari lintasan kapal hasil estimasi EnKF berdasarkan model yang dilengkapi koefisien hidrodinamika menghasilkan rata-rata RMSE posisi x bernilai 0,0000453 dan rata-rata RMSE posisi y bernilai 0,00004905.
======================================================================================================
Designing a mathematical model of ship motion accurately is very important for the smooth operation of the ship in the waters. Mathematical models of ship motion can be utilized in designing control applications and to describe ship maneuverability. One of the components in the mathematical model of ship motion is the ship's hydrodynamic coefficient. The ship's hydrodynamic coefficient is a set of model parameters which, when identified accurately, makes the model able to estimate the ship's motion well. Determining the hydrodynamic coefficient of the ship can be done by do system identification based on the experimental data of the ship. This purpose of this research is to estimate the hydrodynamic coefficient of the ship i-Boat 6 DOF. System identification was carried out using experimental data from the i-Boat equipped with IMU and GPS. The Ensemble Kalman Filter (EnKF) method is used in estimating the model. Then the results from the EnKF are used as input in the Linear Regression method to obtain the value of the ship's hydrodynamic coefficient. The results of this study indicate that the hydrodynamic coefficient values obtained can be used in the mathematical model of the i- Boat motion. This can be seen from the ship trajectory, which was estimated by EnKF method based on a model equipped with hydrodynamic coefficients, which resulted in an average RMSE position of x valued at 0,0000453 and an average RMSE position of y valued at 0,00004905.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | Identifikasi Sistem, Koefisien Hidrodinamika, Ensemble Kalman Filter, Regresi Linier, i-Boat. ================================================================================================================== System Identification, Hydrodynamic Coefficient, Ensemble Kalman Filter, Linear Regression, i-Boat |
| Subjects: | Q Science > QA Mathematics > QA402.3 Kalman filtering. V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering > VM161 Ships--Hydrodynamics |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis |
| Depositing User: | Mirdha Suci Ananda |
| Date Deposited: | 23 Aug 2021 12:40 |
| Last Modified: | 23 Aug 2021 12:40 |
| URI: | http://repository.its.ac.id/id/eprint/89865 |
Actions (login required)
 |
View Item |