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All Journal Journal of Robotics and Control (JRC) International Journal of Robotics and Control Systems
Detak Yan Pratama
Institut Teknologi Sepuluh Nopember, Surabaya
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Mechanical Engineering

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Design of a Control System for Hybrid Quadcopter Tilt Rotor Based on Backward Transition Algorithm Darwito, Purwadi Agus; Agustina, Nilla Perdana; Ahnaf, Hudzaifa Dhiaul; Roosydi, Syahrizal Faried; Pratama, Detak Yan; Biyanto, Totok Ruki
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.22594

Abstract

An Unmanned Aerial Vehicle (UAV) is an unmanned aerial vehicle that can be controlled using either automatic or manual control. UAVs are divided into two types: rotary-wing, which uses rotating propellers to fly the aircraft, and fixed-wing, which uses fixed wings to fly the aircraft. One of the advanced developments in UAV technology is the Hybrid Vertical Take-Off Landing Quadrotor Tiltrotor Aircraft (QTRA) system, which combines the quadrotor UAV system, classified under rotary-wing, with the fixed-wing UAV system. This allows for vertical takeoff and landing as well as the ability to cruise at maximum speed. In the transition between flight modes, from quadcopter to fixed-wing and vice versa, the transition is carried out by changing the thrust direction of the two front UAV rotors from horizontal to vertical and vice versa. The change in thrust angle on the rotor is referred to as a tilt rotor. The problem that arises from changing the aircraft mode from fixed-wing to quadcopter is controlling the UAV's transition mode, which must not lose its lift force. Therefore, the tilt angle must be changed as quickly as possible. To solve this issue, a Hybrid VTOL Quadrotor Tiltrotor aircraft concept was designed with fast response, controlled by a Proportional Derivative (PD) controller. The results of the PD control system response were tested in simulations by observing the X and Z positions of the UAV, which can stabilize the position during the transition. The success criteria targeted for a stable response include a tilting angle with a settling time of 7 seconds, an overshoot height of 16 meters, and a steady-state error approaching zero. From the transition simulation tests, the system response data showed performance with an X-axis settling time of 37 seconds, a steady-state error value of 0.1 meters, and an overshoot of 0.4%.
Indoor Quadcopter Localization Using Fuzzy-Sliding Mode Control for Robust Navigation Darwito, Purwadi Agus; Agustina, Nilla Perdana; Pratama, Detak Yan; Al Farros, Mohammad Naufal; Setiadi, Iwan Cony; Biyanto, Totok Ruki; Imron, Choirul
International Journal of Robotics and Control Systems Vol 5, No 3 (2025)
Publisher : Association for Scientific Computing Electronics and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijrcs.v5i3.1941

Abstract

Growing demand for warehouse automation requires Unmanned Aerial Vehicles (UAVs), particularly quadcopters, to operate autonomously with a high level of precision and reliability. However, indoor localization poses unique challenges due to the absence of Global Positioning System (GPS) signals, making alternative sensors and robust control strategies essential. This study proposes an indoor UAV navigation system that integrates camera and LiDAR sensors with Fuzzy–Sliding Mode Control (Fuzzy-SMC) to enhance stability and reduce the chattering effects commonly associated with Sliding Mode Control. In the proposed method, the camera provides better accuracy for real-time position tracking compared to LiDAR, while fuzzy logic adaptively adjusts the Sliding Mode Control parameters, which serve as the main controller for stabilizing the quadcopter’s nonlinear dynamics. Research methodology includes mathematical modeling of the UAV quadcopter, the design of the Fuzzy-SMC controller, and simulation-based testing for trajectory tracking in indoor environments. Results show that the developed system achieves high accuracy, with error values ranging from 0 to 4.044%, remaining below the acceptable threshold of 5%. These findings demonstrate that integration of a camera with Fuzzy-SMC provides an effective and reliable solution for indoor quadcopter UAV navigation, while future research will focus on optimizing the fuzzy rule base and conducting hardware validation in real warehouse scenarios.
Co-Authors Agustina, Nilla Perdana Ahnaf, Hudzaifa Dhiaul Al Farros, Mohammad Naufal Imron, Choirul Iwan Cony Setiadi, Iwan Cony Purwadi Agus Darwito Roosydi, Syahrizal Faried Totok Ruki Biyanto