Perancangan Sistem Kontrol Fase Forward Transition Pada Autonomous Hybrid quadplane UAV Berbasis Sliding Mode Control-Neural Network (SMCNN)

Fitraturrahim, Fahmi (2024) Perancangan Sistem Kontrol Fase Forward Transition Pada Autonomous Hybrid quadplane UAV Berbasis Sliding Mode Control-Neural Network (SMCNN). Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5009201017-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 October 2026. Download (5MB) | Request a copy

Abstract

Hybrid quadplane UAV memiliki kemampuan VTOL menggunakan keempat propeller vertikal tetapi juga mampu beroperasi pada jangkauan yang jauh menggunakan propeller horizontal. Hal ini dikarenakan UAV ini memiliki switching flight modes, dimana UAV melakukan fase take-off seperti multi-rotor dan fase jelajah layaknya fixed-wing UAV. Pada saat fase transisi ini dibutuhkan sistem kontrol yang tepat agar UAV dapat stabil dan menjaga ketinggiannya. Pada penelitian ini digunakan sistem kendali Sliding Mode Control (SMC) yang mampu menghadapi dinamika UAV dengan diberikan koreksi bobot sliding surface pada SMC menggunakan backpropagation neural network (BPNN) untuk mengurangi efek chattering yang ditimbulkan aturan kontrol SMC. Sistem kendali Sliding Mode Control-Neural Network (SMCNN) ini mampu mengendalikan UAV pada fase forward transition dan mencapai trajectory yang diberikan. Berdasarkan hasil simulasi, menunjukkan bahwa SMCNN memiliki performa yang lebih baik dibanding SMC pada variable yang ditinjau yaitu posisi Z, posisi X, dan sudut pitch. Pada posisi pitch, SMCNN mampu mengurangi efek chattering pada SMC sehingga membuat UAV lebih stabil. Pada posisi Z, Sistem kendali SMC mendapatkan settling time sebesar 7.2s, overshoot 19%, RMSE 0.719, dan ditemukan adanya efek chattering pada respon nya, sedangkan SMCNN mendapatkan settling time sebesar 4.8s, overshoot 8.1%, RMSE 0.121, dan efek chattering berkurang. Pada posisi X, sistem kendali SMC tidak terdapat koreksi BPNN dikarenakan tidak ditemukan adanya efek chattering dengan settling time sebesar 28.1s.
========================================================================================================================
Hybrid quadplane UAV has VTOL capability using all four vertical propellers but is also capable of operating at long range using horizontal propellers. This is because this UAV has switching flight modes, where the UAV carries out a take-off phase like a multi-rotor and a cruise phase like a fixed-wing UAV. During this transition phase, an appropriate control system is needed so that the UAV can be stable and maintain its height. In this research, a Sliding Mode Control (SMC) is used which is able to deal with UAV dynamics by providing sliding surface gain correction on the SMC using a backpropagation neural network (BPNN) to reduce the chattering effect caused by the SMC control rules. This Sliding Mode Control-Neural Network (SMCNN) is capable of controlling the UAV in the forward transition phase and achieving a given trajectory. Based on the simulation results, it shows that SMCNN has better performance than SMC on the variables considered, namely Z position, X position and pitch angle. In the pitch position, SMCNN is able to reduce the chattering effect on the SMC, thereby making the UAV more stable. In position Z, the SMC control system obtained a settling time of 7.2s, overshoot 19%, RMSE 0.719, and found a chattering effect on its response, while SMCNN obtained a settling time of 4.8s, overshoot 8.1%, RMSE 0.121, and the chattering effect was reduced. In X position, the SMC control system does not have BPNN correction because no chattering effects were found with a rise time of 28.1s.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Backpropagation Neural Network (BPNN), Hybrid quadplane UAV, Sliding Mode Control (SMC), Transisi, Backpropagation Neural Network (BPNN), Hybrid quadplane UAV, Sliding Mode Control (SMC), Transition
Subjects:	T Technology > T Technology (General) T Technology > T Technology (General) > T11 Technical writing. Scientific Writing T Technology > T Technology (General) > T57.62 Simulation T Technology > T Technology (General) > T57.83 Dynamic programming T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control
Divisions:	Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Fahmi Fitraturrahim
Date Deposited:	31 Jul 2024 04:05
Last Modified:	31 Jul 2024 04:05
URI:	http://repository.its.ac.id/id/eprint/109431

Actions (login required)

View Item