Kendali Haluan Kapal Menggunakan Metode Unscented Kalman Filter-Nonlinear Model Predictive Control (UKF-NMPC)

Darmawan, Muhammad Syahril Darmawan (2025) Kendali Haluan Kapal Menggunakan Metode Unscented Kalman Filter-Nonlinear Model Predictive Control (UKF-NMPC). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam menjalankan misi pelayaran khususnya pada bidang pertahanan dan keamanan suatu wilayah, kapal perang tentu menghadapi tantangan besar akibat gangguan lingkungan seperti angin, arus laut, dan gelombang. Oleh karena itu, sistem kendali kapal diperlukan agar dapat menjaga kapal tetap berada pada lintasan yang ditetapkan dengan mempertimbangkan gangguan lingkungan yang sulit untuk diprediksi, salah satunya melalui pendekatan metode Unscented Kalman Filter-Nonlinear Model Predictive Control (UKF-NMPC). UKF-NMPC merupakan metode kendali prediktif dari hasil pengembangan Model Predictive Control (MPC) standar yang dirancang khusus untuk menangani sistem nonlinier tanpa melalui proses linierisasi dan proses prediksinya dilakukan oleh UKF dengan mempertimbangkan noise stokastik. Dalam hal ini, noise stokastik merepresentasikan gangguan yang terjadi pada sistem secara acak yang berubah terhadap waktu. Pada penelitian ini menggunakan model matematika gerak kapal perang Extended-Corvette kelas Ship Integrated Geometrical Modularity Approach (SIGMA) dengan mempertimbangkan dua derajat kebebasan, yaitu gerakan sway dan yaw. Penerapan metode kendali UKF-NMPC dilakukan melalui simulasi dengan bantuan perangkat lunak MATLAB R2024b. Hasil simulasi menunjukkan bahwa performa metode kendali UKF-NMPC dapat mengompensasi noise stokastik pada sistem yang bergantung juga dengan nilai kovarian noise stokastik yang diberikan.

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In carrying out maritime missions, particularly in the field of national defense and security, warships inevitably face significant challenges due to environmental disturbances such as wind, ocean currents, and waves. Therefore, a reliable ship control system is essential to ensure the ship remains on its designated trajectory while accounting for unpredictable environmental disturbances. One such approach is the Unscented Kalman Filter–Nonlinear Model Predictive Control (UKF-NMPC) method. UKF-NMPC is a predictive control method developed from the standard Model Predictive Control (MPC), specifically designed to handle nonlinear systems without the need for linearization. Its prediction process is carried out by the Unscented Kalman Filter (UKF), which considers stochastic noise. In this context, stochastic noise represents random, time-varying disturbances affecting the system. This study utilizes a mathematical motion model of a warship classified as an Extended-Corvette of the Ship Integrated Geometrical Modularity Approach (SIGMA) class, taking into account two degrees of freedom (2-DOF), sway and yaw motions. The implementation of the UKF-NMPC control method is carried out through simulations using MATLAB R2024b software. The simulation results demonstrate that the UKF-NMPC control method can effectively compensate for stochastic noise in the system, with its performance also depending on the specified covariance values of the stochastic noise.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Unscented Kalman Filter, Nonlinear Model Predictive Control, Ship Heading Control, Unscented Transform, Stochastic Disturbance, Nonlinear Model Predictive Control, Unscented Transform, Gangguan Stokastik, Gangguan Stokastik
Subjects:	Q Science > QA Mathematics > QA402.3 Kalman filtering.
Divisions:	Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Muhammad Syahril Darmawan
Date Deposited:	04 Aug 2025 10:46
Last Modified:	04 Aug 2025 10:46
URI:	http://repository.its.ac.id/id/eprint/125058

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