Trajectory Tracking menggunakan Fuzzy Predictive Control pada Nonholonomic Mobile Robot

Siregar, Amelia Widhi Natama (2025) Trajectory Tracking menggunakan Fuzzy Predictive Control pada Nonholonomic Mobile Robot. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Mobile robot saat ini semakin berkembang karena kemampuannya yang dapat membantu bahkan menggantikan berbagai pekerjaan manusia. Salah satu tantangan utama dalam pengembangan mobile robot adalah kemampuan untuk mengikuti lintasan secara akurat dengan mempertimbangkan waktu dan kecepatan (trajectory tracking). Pada penelitian tugas akhir ini, telah dirancang metode kontrol trajectory tracking berbasis Model Predictive Control (MPC) yang dikombinasikan dengan Fuzzy Logic Control jenis Takagi-Sugeno (Fuzzy T-S). Fuzzy T-S digunakan untuk mengubah-ubah parameter bobot matriks Q dan R serta memodelkan sistem linier lokal menjadi beberapa subsistem linier global, yang kemudian digunakan sebagai model sistem pada MPC. Rancangan Fuzzy Predictive Control (FPC) menunjukkan kinerja yang lebih baik dibandingkan dengan MPC konvensional. FPC mempersingkat waktu untuk mencapai steady state, menurunkan fungsi biaya, dan menghilangkan osilasi yang terjadi ketika prediction horizon dan control horizon terlalu besar. Berdasarkan pengujian, nilai Mean Squared Error (MSE) FPC adalah 0,0709 untuk lintasan circular, 0,0347 untuk lintasan lemniscate, dan 0,0493 untuk lintasan sinewave. Melalui keunggulan ini, rancangan FPC cocok untuk aplikasi di lingkungan yang dinamis, di mana kontrol optimal dan presisi sangat dibutuhkan.
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Mobile robots are rapidly advancing due to their ability to assist and even replace various human tasks. One of the main challenges in mobile robot development is the ability to follow a trajectory accurately while considering time and speed (trajectory tracking). In this research, a trajectory tracking control method was designed based on Model Predictive Control (MPC) combined with Takagi-Sugeno Fuzzy Logic Control (Fuzzy T-S). Fuzzy T-S was used to adjust the weight parameters of matrices Q and R and to model local linear systems into multiple global linear subsystems, which were then applied as system models in MPC. The Fuzzy Predictive Control (FPC) design demonstrated better performance compared to conventional MPC. FPC shortened the time to reach the steady state, reduced cost function values, and eliminated oscillations caused by large prediction and control horizons. Based on testing, the Mean Squared Error (MSE) values for FPC were 0.0709 for circular trajectories, 0.0347 for lemniscate trajectories, and 0.0493 for sinewave trajectories. These advantages make the FPC design suitable for applications in dynamic environments where optimal and precise control is highly required.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Trajectory Tracking, Mobile Robot, Model Predictive Control, Fuzzy Logic
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ211 Robotics. T Technology > TJ Mechanical engineering and machinery > TJ211.4 Robot motion T Technology > TJ Mechanical engineering and machinery > TJ211.415 Mobile robots T Technology > TJ Mechanical engineering and machinery > TJ217.6 Predictive Control
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	Amelia Widhi Natama Siregar
Date Deposited:	23 Jan 2025 06:54
Last Modified:	23 Jan 2025 06:54
URI:	http://repository.its.ac.id/id/eprint/116737

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