Simulation-based Assessment of Quadrotor Linear Control Schemes
Osama M. Al-Habahbeh1, Ismaeel H. Al-Abdullah2, Dawod N. Al-Dweik3, Mohammad A. Abu-Aqlah4, Mustafa A. Al-Khawaldeh5
1Dr. Osama M. Al-Habahbeh, B.Sc degree in Mechanical Engineering from the University of Jordan in 1995.
2Ismail Alabdullah, Department of Mechatronics Engineering at the Faculty of Engineering and Technology in Jordan University.
3Dawod Nedal AL Dweik, Department of Mechatronics Engineering at the Faculty of Engineering and Technology in Jordan University.
4Mohammad Ahmed. Abu-Aqlah Department of mechatronics at Jordan University.
5Dr. Mustafa Awwad Al-Khawaldeh, assistant professor in the Department of Mechatronics Engineering at Philadelphia University in Jordan.
Manuscript received on 07 August 2019. | Revised Manuscript received on 14 August 2019. | Manuscript published on 30 September 2019. | PP: 3654-3662 | Volume-8 Issue-3 September 2019 | Retrieval Number: C4713098319/2019©BEIESP | DOI: 10.35940/ijrte.C4713.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This work aims at finding the most suited control scheme for a typical quad-rotor. Selecting the appropriate controller is essential to achieve system stability. The most common control schemes are compared in terms of their performance in hovering mode. The quad-rotor propellers are modeled based on both momentum theory and blade element theory. The model describing the six-degrees of freedom system is used to develop a control strategy using different types of controllers such as PID, Fuzzy, Optimal, LQ), as well as LQR controller. The current work is confined to linear control schemes in hovering flight mode, where the comparison is based on achieving stable attitude in hovering. The simulation results show that the LQR controller is the most efficient control method to minimize the steady-state error.
Keywords: Modeling and Simulation, Quad-Rotor Control, Fuzzy-PID Logic, LQR Control
Scope of the Article: Simulation Optimization and Risk Management