Analisis Optimalisasi Kontrol Pid Pada Quadcopter Dengan Algoritma Particle Swarm Optimization (PSO) Dan Adaptive Particle Swarm Optimization (APSO)

Ardy, Mochamad Misbachul Munir Ardy (2025) Analisis Optimalisasi Kontrol Pid Pada Quadcopter Dengan Algoritma Particle Swarm Optimization (PSO) Dan Adaptive Particle Swarm Optimization (APSO). Masters thesis, Institut Teknologi Sepuluh Nopember.

	Text Thesis Lengkap.pdf - Accepted Version Restricted to Repository staff only Download (3MB) | Request a copy
	Text 6002221011-Master_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 April 2027. Download (3MB) | Request a copy

Abstract

Quadcopter, atau quadrotor, adalah kendaraan udara tak berawak dengan empat rotor yang memilki dinamika nonlinier. Penelitian ini berfokus pada optimalisasi parameter kontroler Proporsional Integral Derivatif (PID) untuk meningkatkan performa kendali quadcopter, yang dievaluasi berdasarkan stabilitas, waktu respons, dan akurasi pelacakan lintasan. Dua algoritma optimasi metaheuristik, yaitu Particle Swarm Optimization (PSO) dan Adaptive Particle Swarm Optimization (APSO), diterapkan untuk menala parameter kontroler PID. Sebagai perbandingan, metode Ziegler-Nichols digunakan untuk mendapatkan parameter kontroler PID. Penelitian ini menggunakan model fungsi transfer quadcopter yang telah disederhanakan dengan tingkat akurasi 83%. Analisis kestabilan, keterkontrolan, dan keteramatan model dilakukan dan menunjukkan bahwa sistem stabil asimtotik, terkontrol, dan teramati. Performa kontroler PID yang diperoleh dari ketiga metode (PSO, APSO, dan Ziegler-Nichols) dievaluasi menggunakan fungsi objektif Integral Time Absolute Error (ITAE) dan Integral Time Squared Error (ITSE). Hasil simulasi menunjukkan bahwa metode PSO dan APSO dengan fungsi objektif ITSE menunjukkan performa terbaik, dengan nilai error yang kecil, rise time dan peak time yang cepat, serta overshoot dan settling time yang rendah dari pada Ziegler-Nichols Close Loop. Hasil penelitian ini berkontribusi pada pengembangan sistem kendali quadcopter yang lebih efisien dan efektif, serta menjadi panduan pemilihan teknik optimasi yang paling sesuai untuk aplikasi quadcopter tertentu.
==================================================================================================================================
A quadcopter, or quadrotor, is an unmanned aerial vehicle with four rotors that has nonlinear dynamics. This research focuses on optimising the parameters of the Proportional Integral Derivative (PID) controller to improve the control performance of the quadcopter, which is evaluated based on stability, response time and trajectory tracking accuracy. Two metaheuristic optimisation algorithms, namely Particle Swarm Optimisation (PSO) and Adaptive Particle Swarm Optimisation (APSO), are applied to tune the PID controller parameters. For comparison, the ZieglerNichols method is used to obtain the PID controller parameters. This study uses a simplified quadcopter transfer function model with an accuracy rate of 83%. Stability, controllability, and observability analyses of the model were conducted and showed that the system is asymptotically stable, controllable, and observable. The performance of the PID controllers obtained from the three methods (PSO, APSO, and Ziegler-Nichols) is evaluated using the Integral Time Absolute Error (ITAE) and Integral Time Squared Error (ITSE) objective functions. Simulation results show that the PSO and APSO methods with the ITSE objective function produce the best performance, with small error values, fast rise time and peak time, and low overshoot and settling time than the Ziegler-Nichols Close Loop. The results of this study contribute to the development of a more efficient and effective quadcopter control system, and guide the selection of the most suitable optimisation technique for a particular quadcopter application.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Quadcopter, Kontrol PID, Particle Swarm Optimization (PSO), Adaptive Particle Swarm Optimization (APSO), Ziegler-Nichols, Kestabilan, Keterkontrolan, Keteramatan, ITAE, ITSE
Subjects:	Q Science > QA Mathematics Q Science > QA Mathematics > QA401 Mathematical models.
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44101-(S2) Master Thesis
Depositing User:	MOCHAMAD MISBACHUL MUNIR ARDY
Date Deposited:	20 Feb 2025 02:59
Last Modified:	20 Feb 2025 02:59
URI:	http://repository.its.ac.id/id/eprint/118129

Actions (login required)

View Item