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Decentralized Backstepping Control of a Quadrotor with Tilted-rotor under Wind Gusts

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Abstract

Conventional unmanned aerial vehicles, quadrotor have a plethora of applications for civilian and military purposes. Quadrotors as the name implies usually have four input variables (fixed rotors) which are used to drive six outputs (i.e., 3 translational and 3 rotational motions), and this leads to coupling between motions. Tilt- rotor quadrotors are more versatile because they have more input variables to independently control its orientation and position without coupling. In this paper, a decentralized backstepping control approach is used to generate a new set of inputs capable of independently and simultaneously achieve decoupling of motions while rejecting wind disturbances. The tiltrotor quadrotor dynamic is first decentralized to achieve six subsystems, then controller inputs for each subsystem are generated via Lyapunov based backstepping method whereby the controller parameters are optimized by Differential Evolution (DE) technique. This system exhibits robustness capability because it is able to reject external disturbances.

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Authors and Affiliations

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Correspondence to Abdul-Wahid A. Saif.

Additional information

Recommended by Associate Editor Yang Tang under the direction of Editor Hyun-Seok Yang. The authors would like to thank DSR at KFUPM for the support of this work under the project No. IN141048.

Abdul-Wahid A. Saif received his Ph.D. from control and and Instrumentation Group, Department of Engineering, Leicester University, U.K., an M.Sc. from Systems Engineering Department, and a B.Sc. from Physics Department, King Fahd University of Petroleum and Minerals (KFUPM), Dhahran S.A. Dr. Saif is currently an Associate Professor of Control and Instrumentation in Systems Engineering Department (SE) at KFUPM. Dr. Saif research interest is Simultaneous and Strong Stabilization, Robust Control and H¥-optimization, Wire and Wireless Networked Control, Instrumentation and Computer Control. Dr. Saif taught several courses in Modeling and Simulation, Digital Control, Digital Systems, Microprocessor and Microcontrollers in automation, Optimization, Numerical Methods, PLC’s, Process Control and Control System Design. Dr. Saif has published more than 75 papers in reputable journals and conferences.

Abdulrahman Aliyu received the B.Eng. degree in Electrical Engineering from Bayero University Kano, Nigeria. He also recieved his M.Sc. degree in Systems and Control Engineering from King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia in 2016, where he is currently working towards a Ph.D. degree in the same feild. His research areas includes, Integer/Fractional Order Control, Robotics, Multiagent and Complex Systems, Artificial Intelligence and Machine Learning.

Mujahed Al Dhaifallah received his B.S. and M.S. degrees in systems engineering from King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, and his Ph.D. degree in electrical and computer engineering from University of Calgary, Calgary, Canada. He has been an assistant professor of systems engineering with King Fahd University of Petroleum and Minerals, Saudi Arabia since 2009. Currently, he is working as dean of college of engineering at Wadi Al-Dawaser, Prince Sattam bin Abdulaziz University, Saudi Arabia. His main research in the field of Systems Identification, Control and Machine learning.

Moustafa Elshafei obtained his Ph.D. in Electrical Engineering from McGill in 1982 (Dean List), Canada. Since then he has accumulated over 24 years of Academic experience and 9 years of industrial experience. He is inventor/coinventor of 20 USA and international patents, Author/Co-author of 3 books, and published over 150 articles in international journals and professional conferences in the fields of intelligent instrumentation, digital signal processing, artificial intelligence, and industrial control/automation systems.

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Saif, AW.A., Aliyu, A., Dhaifallah, M.A. et al. Decentralized Backstepping Control of a Quadrotor with Tilted-rotor under Wind Gusts. Int. J. Control Autom. Syst. 16, 2458–2472 (2018). https://doi.org/10.1007/s12555-017-0099-x

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  • DOI: https://doi.org/10.1007/s12555-017-0099-x

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