Rancang Bangun Sistem Kendali Pada Autonomous Quadcopter Menggunakan LQG Controller Untuk Melakukan Obstacle Avoidance

Alfathrah, Bima Dardaa (2022) Rancang Bangun Sistem Kendali Pada Autonomous Quadcopter Menggunakan LQG Controller Untuk Melakukan Obstacle Avoidance. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 02311840000006-Undergraduate_Thesis (1).pdf - Accepted Version Restricted to Repository staff only until 1 March 2025. Download (4MB) | Request a copy

Abstract

Teknologi pada UAV yang terus berkembang menjadikan banyak kegunaan di berbagai industri. UAV perlu memiliki kemampuan mengubah jalur yang diberikan terhadap kondisi lingkungan penerbangan. Penelitian pada tugas akhir ini menyajikan implementasi dari Linear Quadratic Gaussian (LQG) Controller dan sensor LiDAR pada quadcopter yang digunakan untuk menghindari obstacle. LQG merupakan paduan antara Linear Quadratic Regulator (LQR) dengan Kalman Filter sebagai State Estimator. Hasil estimasi oleh Kalman Filter dibandingkan terhadap nilai aktual pengukurannya dengan meninjau nilai Mean Square Error. Posisi linear dan posisi angular merupakan variabel yang dikendalikan dalam sistem pengendali LQG untuk melakukan Obstacle Avoidance. Beberapa pengujian yang telah dilakukan antara lain, uji open loop, uji closed loop, uji quadcopter tanpa halangan, dan uji quadcopter dengan halangan. Sistem kendali LQG yang dirancang menghasilkan performansi pengendali rise time, settling time, dan Maximum Overshoot pada pengujian closed loop yang optimal sebesar 2.1315 s, 19.9733 s, 17.1142 % untuk gerakan translasi dan 1.5323 s, 5.9798 s, 10.2958 % untuk gerakan rotasi. Hasil pengujian menunjukkan bahwa quadcopter mampu untuk mengikuti jalur referensi penerbangan dan algoritma obstacle avoidance yang dirancang menghasilkan quadcopter yang mampu untuk menghindari obstacle. Hasil pengujian menunjukkan matriks Q dan R pada Gain Regulator dan Kalman filter dapat mempengaruhi quadcopter dalam melakukan penghindaran.
=================================================================================================================================
The ever-evolving technology in UAVs has made many uses in various industries. UAVs need to have the ability to change the path given to the conditions of the aviation environment. The research in this final project presents the implementation of the Linear Quadratic Gaussian (LQG) Controller and LiDAR sensors on the quadcopter used to avoid obstacles. The results of the estimate by Kalman Filter are compared against the actual value of the measurement by reviewing the Mean Square Error value. LQG is a combination of Linear Quadratic Regulator (LQR) with Kalman Filter as a State Estimator. Linear position and angular position are variables that are controlled in the LQG control system to perform Obstacle Avoidance. Some of the tests that have been carried out include the open loop test, the closed loop test, the quadcopter test without hindrance, and the quadcopter test with obstruction. The designed LQG control system produces rise time, settling time, and Maximum Overshoot control performance in optimal closed loop tests of 2.1315 s, 19.9733 s, 17.1142% for translational motion and 1.5323 s, 5.9798 s, 10.2958% for rotational motion. The test results show that the quadcopter can follow the flight reference path and the obstacle avoidance algorithm designed produces a quadcopter that is able to avoid obstacles. The test results show that the Q and R matrices on the Gain Regulator and Kalman filters can affect the quadcopter in carrying out avoidance.

Item Type:	Thesis (Other)
Additional Information:	RSF 629.892 Alf r-1 2022
Uncontrolled Keywords:	Quadcopter, Autonomous, Obstacle Avoidance, LQG
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles.
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Anis Wulandari
Date Deposited:	05 Jul 2024 03:37
Last Modified:	05 Jul 2024 03:37
URI:	http://repository.its.ac.id/id/eprint/108134

Actions (login required)

View Item