Perencanaan Jalur Dinamis Unmanned Surface Vehicle Berbasis Genetic Algorithm Dengan Sistem Pemanduan Sliding Curve

Pratama, Fian Ilham (2020) Perencanaan Jalur Dinamis Unmanned Surface Vehicle Berbasis Genetic Algorithm Dengan Sistem Pemanduan Sliding Curve. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Unmanned Surface Vehicle (USV) adalah kapal tanpa awak yang dikendalikan melalui sistem remote control dari jarak jauh (manual) maupun secara otomatis (autopilot), bergerak akibat gaya dorong yang dihasilkan oleh mesin thruster dan dapat berbelok akibat adanya sudut defleksi kemudi. USV harus memiliki kemampuan untuk merencanakan lintasan global dengan indikator jarak, path smoothness dan dapat menghindari obstacle dari situasi berbahaya lokal yang tidak dapat diprediksi dan sangat dinamis. Sistem perencanaan jalur USV menjadi bagian penting agar kapal dapat membuat lintasan dengan jarak perjalanan minimum sesuai navigasi yang diinginkan sekaligus dapat menghindari berbagai obstacle dinamis yang berpotensi terjadi tabrakan. Untuk dapat melakukan perencanaan jalur dinamis USV, digunakan metode Genetic Algorithm dengan sistem pemanduan sliding curve dan kontroler PID MRAC. Penggunaan metode ini dapat memberikan performa lintasan kapal yang mulus (smoothness) dengan jarak minimum. Pada penelitian ini, USV 6 Degreee of Freedom (derajat kebebasan) dengan panjang 6 meter digunakan untuk memvalidasi algoritma. Algoritma genetika yang diterapkan dalam penelitian ini bisa menghasilkan panjang lintasan terpendek dalam sebuah map 400x400 meter persegi dengan obstacle statis dan dinamis. Dalam lingkungan dinamis, proses path re-planning yang dilakukan dalam 0,98 detik mampu menemukan sebuah path baru yang tidak menabrak obstacle. Untuk keperluan validasi algoritma, dilakukan simulasi menggunakan software MATLAB dengan parameter kapal riil. ========================================================================================================== Unmanned Surface Vehicle (USV) is an unmanned ship that is controlled through a remote control system (manual) or automatic control system (autopilot), move due to the thrust force from thruster machine and can turning due to the deflection angle of rudder. USV must have the ability to plan a global trajectory with indicator such as distance, path smoothness and be able to avoid obstacles from local situations that are unpredictable and very dynamic. The USV path planning system is an important part so that the ship can make the trajectory with the minimum travel distance according to the desired navigation while at the same time avoiding various dynamic obstacles that have the potential for collisions. To be able to do dynamic USV path planning, the Genetic Algorithm method with a sliding curve guidance system and PID MRAC controller is used. The use of this method gives smooth ship track performance with a minimum distance. In this study, USV 6 Degree of Freedom with 6 meters length is used to validate the algorithm. The genetic algorithm applied in this study is capable of finding a shortest path length in a 400x400 square meter map with static and dynamic obstacles. In a dynamic environment, the path re-planning process that takes place in 0,98 seconds is able to find a new path that does not collide the obstacles. For the purposes of algorithm validation, the simulation is performed using MATLAB software with real ship parameters.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: USV, Genetic Algorithm, PID MRAC, Path Planning, Dynamic and static obstacle, Sliding Curve, Guidance System, USV, Algoritma Genetika, PID MRAC, Path Planning, Obstacle statis dan dinamis, Sliding Curve, Sistem Pemanduan
Subjects: T Technology > TE Highway engineering. Roads and pavements > TE228.3 Intelligent transportation systems.
Divisions: Faculty of Electrical Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: FIAN ILHAM PRATAMA
Date Deposited: 12 Aug 2020 09:17
Last Modified: 12 Aug 2020 09:17
URI: https://repository.its.ac.id/id/eprint/77639

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