Perancangan Sistem Kendali Quadcopter Menggunakan Metode Robust Self-Tuning PID Controller Based On Fuzzy Logic

Ainatul Iza, Belgis (2022) Perancangan Sistem Kendali Quadcopter Menggunakan Metode Robust Self-Tuning PID Controller Based On Fuzzy Logic. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Saat ini, quadcopter sangat popular karena telah banyak diimplementasikan dalam berbagai macam aspek. Sehingga quadcopter menarik minat peneliti salah satunya adalah peneliti bidang sistem kontrol. Berbagai macam algoritma kontrol dikembangkan untuk menjaga kestabilan quadcopter pada lintasan tertentu. Oleh karena itu, untuk mendukung perkembangan algoritma kontrol tersebut, pada penelitian ini membahas perancangan Robust Self-Tuning PID controller based on Fuzzy Logic. Sistem kontrol tersebut dapat memberi lebih banyak kelebihan jika dibanding metode kontrol konvensional seperti PID controller. Robust Self-Tuning PID controller based on Fuzzy Logic cocok untuk menyelesaikan sistem yang taklinier dan parameter yang tidak pasti. Guna mendapatkan performasi yang bagus, penulis mendesain beberapa sistem kontrol. Untuk mempertahankan gerak translasi (sumbu X dan Y) pada quadcopter, penelitian ini merancang sistem kontrol Robust Self-Tuning PID, Robust Self-Tuning Fuzzy-PI, Robust Self-Tuning Fuzzy-PD dan Robust Self-Tuning Fuzzy-PID. Sedangkan gerak rotasi (sudut roll, pitch dan yaw) di kendalikan menggunakan sistem kontrol Robust Self-Tuning PID dan Robust Self-Tuning Fuzzy-PID. Selanjutnya, sistem akan diberi gangguan luar dalam bentuk angin untuk memastikan bahwa sistem kontrol masih dapat menjaga kestabilan gerak quadcopter saat terbang.
Hasil simulasi menunjukkan perbandingan beberapa sistem kontrol untuk gerak rotasi maupun translasi pada quadcopter. Untuk gerak rotasi, sistem kontrol Fuzzy-PD memiliki selisih nilai 0,1 dari referensi yang diinginkan pada detik ke-10, sedangkan PID memiliki selisih nilai 0,2 pada detik yang sama. Sehingga dapat dikatakan bahwa Fuzzy-PD dapat menjaga kestabilan gerak rotasi lebih baik jika dibandingkan dengan PID ketika sistem kontrol tidak diberi noise. Namun ketika diberi noise, sinyal kontrol PID memiliki respon dua kali lebih cepat dibanding Fuzzy-PD untuk mendekati referensi yang diinginkan.
Dalam menjaga kestabilan gerak translasi pada quadcopter, sistem kontrol Fuzzy-PD mampu mencapai referensi yang diinginkan lebih cepat ketika tidak diberi noise. Selisih nilai sistem kontrol Fuzzy-PD dengan referensi adalah 0,01. Akan tetapi saat sistem kontrol diberi noise, Fuzzy-PID memiliki performa yang paling bagus dalam menjaga kestabilan gerak translasi pada quadcopter. sistem kontrol Fuzzy-PID dapat mencapai referensi yang diinginkan setelah 3 detik untuk gerak translasi sumbu x dan 5 detik untuk gerak translasi sumbu y.
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Currently, quadcopters are very popular because they have been
implemented in various aspects. So that the quadcopter attracts the interest of
researchers, one of which is a researcher in the field of control systems. Various
control algorithms have been developed to maintain the stability of the quadcopter
on a certain path. Therefore, to support the development of the control algorithm,
this study discusses the design of a Robust Self-Tuning PID controller based on
Fuzzy Logic. The control system can provide more advantages when compared to
conventional control methods such as PID controllers. Robust Self-Tuning PID
controller based on Fuzzy Logic is suitable for solving nonlinear systems and
uncertain parameters. In order to get good performance, the author designed several
control systems. To maintain the translational motion (X and Y axes) on the
quadcopter, this study designed a control system for Robust Self-Tuning PID,
Robust Self-Tuning Fuzzy-PI, Robust Self-Tuning Fuzzy-PD and Robust Self-
Tuning Fuzzy-PID. While the rotational motion (roll, pitch and yaw angle) is
controlled using the Robust Self-Tuning PID and Robust Self-Tuning Fuzzy-PID
control systems. Furthermore, the system will be given external disturbance in the
form of wind to ensure that the control system can still maintain the stability of the
quadcopter's motion while hovering.
The simulation results show the comparison of several control systems for
rotational and translational motion of the quadcopter. For rotational motion, the
Fuzzy-PD control system has a difference value of 0.1 from the desired reference
at the 10th second, while the PID has a different value of 0.2 at the same time. So,
it can be said that Fuzzy-PD can maintain the stability of rotational motion better
than PID when the control system is not given noise. However, when given noise,
the PID control signal has a response twice as fast as Fuzzy-PD to approach the
desired reference.
In maintaining the stability of translational motion of the quadcopter, the
Fuzzy-PD control system is able to achieve the desired reference faster when it is
not given noise. The difference of the Fuzzy-PD control system with the reference
is 0.01. However, when the control system is given noise, Fuzzy-PID has the best
performance in maintaining the stability of the translational motion of the
quadcopter. Fuzzy-PID control system can reach the desired reference after 3
seconds for x-axis translational motion and 5 seconds for y-axis translational
motion.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	UAV, Quadcopter, Drone, Fuzzy Logic, PID Controller, Control System, Non-Linier, Fuzzy-PID, Logika Fuzzy, Kontrol PID, Sistem Kontrol
Subjects:	Q Science > QA Mathematics > QA401 Mathematical models. Q Science > QA Mathematics > QA76.6 Computer programming. Q Science > QA Mathematics > QA9.64 Fuzzy logic
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44101-(S2) Master Thesis
Depositing User:	Belgis Ainatul Iza
Date Deposited:	09 Feb 2022 07:43
Last Modified:	31 Oct 2022 01:37
URI:	http://repository.its.ac.id/id/eprint/93390

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