Kontrol Elevator Pesawat Terbang dengan Simulasi X-Plane Menggunakan Model Predictive Control (MPC)

Nabiha, Calilanisa (2024) Kontrol Elevator Pesawat Terbang dengan Simulasi X-Plane Menggunakan Model Predictive Control (MPC). Diploma thesis, Institut Teknologi Sepuluh Nopember.

Text 5022201066-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2026. Download (7MB)

Abstract

Pengaturan Flight Control System pada pesawat terbang telah banyak dilakukan, khususnya menggunakan metode Model Predictive Control karena kontroler tersebut dapat memprediksi perilaku masa depan sistem, melakukan optimasi pada setiap waktu, penanganan kendala seperti batasan sudut kemiringan, kecepatan, dan posisi pesawat terbang. Oleh karena itu, pengendalian elevator pada pesawat terbang merupakan salah satu aspek penting dalam memastikan keselamatan dan efisiensi penerbangan. Dalam upaya untuk meningkatkan responsivitas pengendalian elevator, diusulkan penggunakan Model Predictive Control berbasis simulasi X-Plane. X-Plane merupakan simulator pesawat terbang yang menyediakan lingkungan penerbangan yang realistis dan mendetail yang dapat membantu sebelum menerapkan kontroler secara ril. Model Predictive Control digunakan untuk mengoptimalkan perilaku elevator dan mengatur kontrol secara otomatis. Implementasi Model Predictive Control pada penelitian ini menunjukkan hasil akhir yang baik. Hasil akhir menunjukkan nilai output nilai elevator sebesar 0.0402 dengan nilai referensi pitch angle sebesar 7-9 derajat pada saat 3 detik dan 15-16 derajat saat 6.5 detik yang didapatkan dari Boeing Manual Book yang akan disimulasikan di X-Plane dengan nilai MSE terkecil yaitu sebesar 1.204. Hasil MSE tersebut menggunakan kontrol horizon Np sebesar 20 dan prediksi kontrol Nc sebesar 8. Pesawat yang disimulasikan pada X-Plane dapat melakukan gerak lepas landas dengan baik menggunakan hasil kontroler Model Predictive Control (MPC).
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Flight Control System settings on aircraft have been widely carried out, especially using the Model Predictive Control method because the controller can predict the future behavior of the system, perform optimization at any time, handling constraints such as tilt angle constraints, speed, and aircraft position. Therefore, controlling the elevator on an airplane is one of the important aspects in ensuring flight safety and efficiency. In an effort to improve the responsiveness of elevator control, the use of X-Plane simulation-based Model Predictive Control is proposed. X-Plane is an airplane simulator that provides a realistic and detailed flight environment that can be helpful before implementing a real controller. Model Predictive Control is used to optimize the elevator behavior and set the control automatically. The implementation of Model Predictive Control in this research shows good final results. The final result shows the output value of the elevator value of 0.0402 with a pitch angle reference value of 7-9 degrees at 3 seconds and 15-16 degrees at 6.5 seconds obtained from the Boeing Manual Book which will be simulated in X-Plane with the smallest MSE value of 1,204. The MSE results use a control horizon Np of 20 and a control prediction Nc of 8. The aircraft simulated in X-Plane can perform takeoff motion properly using the Model Predictive Control (MPC) results.

Item Type:	Thesis (Diploma)
Uncontrolled Keywords:	Model Predictive Control (MPC), Elevator, X-Plane Model Predictive Control (MPC), Elevator, X-Plane
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL521 Aerodynamics, Hypersonic. T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL671.9 Airplanes--Maintenance and Repair T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL696.C6 Airplanes--Collision avoidance
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	Calilanisa Nabiha
Date Deposited:	07 Aug 2024 06:40
Last Modified:	07 Aug 2024 06:40
URI:	http://repository.its.ac.id/id/eprint/110804

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