Hostname: page-component-848d4c4894-x5gtn Total loading time: 0 Render date: 2024-05-05T17:38:48.863Z Has data issue: false hasContentIssue false

Enhanced backstepping control for an unconventional quadrotor under external disturbances

Published online by Cambridge University Press:  28 July 2022

A. Belmouhoub*
Affiliation:
Materials and Electronic Systems Laboratory, University of Mohamed El Bachir El Ibrahimi, Bordj Bou Arreridj, Algeria
S. Medjmadj
Affiliation:
Laboratory of Control University of Setif and University of Bordj Bou Arreridj, Algeria
Y. Bouzid
Affiliation:
Complex Systems Control and Simulators (CSCS) laboratory, Ecole Militaire Polytechnique, Bordj el Bahri, Algiers, Algeria
S. H. Derrouaoui
Affiliation:
Complex Systems Control and Simulators (CSCS) laboratory, Ecole Militaire Polytechnique, Bordj el Bahri, Algiers, Algeria
M. Guiatni
Affiliation:
Complex Systems Control and Simulators (CSCS) laboratory, Ecole Militaire Polytechnique, Bordj el Bahri, Algiers, Algeria
*
*Corresponding author. Email: belmouhoub.amina@gmail.com

Abstract

Robust control of non-linear systems is a challenging task, notably in the presence of external disturbances and uncertain parameters. The main focus of this paper is to solve the trajectory tracking problem of an unconventional quadrotor with rotating arms (also known as a foldable drone), while overcoming some of the challenges associated with this type of vehicle. Therefore, in a first step, the model of this vehicle is presented, taking into account the change of the inertia, the centre of gravity, and the control matrix. The theoretical foundations of backstepping control, based on the finite time Lyapunov stability theory and enhanced by a Super-Twisting algorithm, are then discussed. Numerical simulations are performed to demonstrate the efficiency of the suggested control approach. Finally, a qualitative and quantitative comparative study of the proposed controller with the conventional backstepping controller is performed. Overall, the obtained results show that the proposed control strategy outperforms in terms of accuracy and resilience.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Derafa, L., Ouldali, A., Madani, T. and Benallegue, A. Non-linear control algorithm for the four rotors UAV attitude tracking problem, Aeronaut. J., 2011, 115, (1165), pp 175185.CrossRefGoogle Scholar
Yuan, S., Wang, H. and Xie, L. Survey on localization systems and algorithms for unmanned systems, Unmanned Syst., 2021, 9, (2), pp 129163.CrossRefGoogle Scholar
Mokhtari, M.R. and Cherki, B. A new robust control for minirotorcraft unmanned aerial vehicles, ISA Trans., 2015, 56, pp 86101.CrossRefGoogle ScholarPubMed
Derrouaoui, S.H., Bouzid, Y., Guiatni, M., Kada, H., Dib, I. and Moudjari, N. Backstepping controller applied to a foldable quadrotor for 3d trajectory tracking, In ICINCO, pp 537544, 2020.CrossRefGoogle Scholar
Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S. and Ruffier, F. X-morf: A crash-separable quadrotor that morfs its x-geometry in flight, In 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), pp 222227. IEEE, 2017.CrossRefGoogle Scholar
Derrouaoui, S.H., Bouzid, Y., Guiatni, M. and Belmouhoub, A. Trajectory tracking of a reconfigurable multirotor using optimal robust sliding mode controller, 2022.Google Scholar
Falanga, D., Mueggler, E., Faessler, M. and Scaramuzza, D. Aggressive quadrotor flight through narrow gaps with onboard sensing and computing using active vision, In International Conference on Robotics and Automation (ICRA), pp 57745781. IEEE, 2017.CrossRefGoogle Scholar
Mintchev, S. and Floreano, D. Adaptive morphology: A design principle for multimodal and multifunctional robots, Robot. Automat. Mag., 2016, 23, (3), pp 4254.CrossRefGoogle Scholar
Floreano, D. and Wood, R.J., technology and the future of small autonomous drones, Nature, 2015, 521, (7553), pp 460466.CrossRefGoogle ScholarPubMed
Caballero, A., Suarez, A., Real, F., Vega, V.M., Bejar, M., Rodriguez-Castaño, A. and Ollero, A. First experimental results on motion planning for transportation in aerial long-reach manipulators with two arms, In International Conference on Intelligent Robots and Systems (IROS), pp 84718477. IEEE, 2018.CrossRefGoogle Scholar
Yilmaz, E., Zaki, H. and Unel, M. Nonlinear adaptive control of an aerial manipulation system, In 18th European Control Conference (ECC), pp 39163921. IEEE, 2019.CrossRefGoogle Scholar
Derrouaoui, S.H., Bouzid, Y., Guiatni, M., Dib, I. and Moudjari, N. Design and modeling of unconventional quadrotors, In 28th Mediterranean Conference on Control and Automation (MED), pp 721726. IEEE, 2020.CrossRefGoogle Scholar
Kamil, Y., Hazry, D., Wan, K., Razlan, Z.M. and Shahriman, A.B. Design a new model of unmanned aerial vehicle quadrotor using the variation in the length of the arm, In International Conference on Artificial Life and Robotics (ICAROB), Miyazaki, Japan, pp 1922, 2017.CrossRefGoogle Scholar
Hazry, D., Wan, K. and Razlan, Z.M. A novel val: Quadrotor control technique for trajectory tracking based on varying the arm’s length, ARPN J. Eng. Appl. Sci., 2016, 11, (15), pp 91959204.Google Scholar
Derrouaoui, S.H., Bouzid, Y., Guiatni, M. and Dib, I. A comprehensive review on reconfigurable drones: Classification, characteristics, design and control technologies, Unmanned Syst., 2021, pp 127.Google Scholar
Sheng, S. and Sun, C. Control and optimization of a variable-pitch quadrotor with minimum power consumption, Energies, 2016, 9, (4), p 232.CrossRefGoogle Scholar
Muliadi, J. The analysis of unconventional aircraft flight dynamics model by linearizing its equation of motion as applied in BPPT’s V-tail configuration UAV “Gagak”, In AIP Conference Proceedings, p 020060. AIP Publishing LLC, 2016.Google Scholar
Invernizzi, D., Giurato, M., Gattazzo, P. and Lovera, M. Full pose tracking for a tilt-arm quadrotor UAV, In Control Technology and Applications (CCTA), pp 159164. IEEE, 2018.CrossRefGoogle Scholar
Farrell, M., Jackson, J., Nielsen, J., Bidstrup, C. and McLain, T. Error-state LQR control of a multirotor UAV, In International Conference on Unmanned Aircraft Systems (ICUAS), pp 704711. IEEE, 2019.CrossRefGoogle Scholar
Hamadi, H., Lussier, B., Fantoni, I., Francis, C. and Shraim, H. Observer-based super twisting controller robust to wind perturbation for multirotor UAV. In International Conference on Unmanned Aircraft Systems (ICUAS), pp 397405. IEEE, 2019.CrossRefGoogle Scholar
Sartori, D., Quagliotti, F., Rutherford, M.J. and Valavanis, K.P. Design and development of a backstepping controller autopilot for fixed-wing uavs. Aeronaut. J., 2021, 125, (1294), pp 20872113.CrossRefGoogle Scholar
Gao, T.Y., Wang, D.D., Tao, F. and Ge, H.L. Control of small unconventional UAV based on an on-line adaptive ADRC system, In Applied Mechanics and Materials, pp 12061211. Trans Tech Publ, 2014.Google Scholar
De Almeida, M.M. and Raffo, G.V. Nonlinear control of a Tiltrotor UAV for load transportation, IFAC-PapersOnLine, 2015, 48, (19), pp 232237.CrossRefGoogle Scholar
Andrade, R., Raffo, G.V. and Normey-Rico, J.E. Model predictive control of a tilt-rotor UAV for load transportation, In European Control Conference (ECC), pp 2165–2170. IEEE, 2016.CrossRefGoogle Scholar
Willis, J., Johnson, J. and Beard, R.W. State-dependent LQR control for a Tilt-rotor UAV, In American Control Conference (ACC), pp 41754181. IEEE, 2020.Google Scholar
Wallace, D.A. Dynamics and control of a quadrotor with active geometric morphing, PhD thesis, 2016.Google Scholar
Barbaraci, G. Modeling and control of a quadrotor with variable geometry arms, Unmanned Veh. Syst., 2015, 3, (2), pp 3557.CrossRefGoogle Scholar
Falanga, D., Kleber, K., Mintchev, S., Floreano, D. and Scaramuzza, D. The foldable drone: A morphing quadrotor that can squeeze and fly, Robot. Automat. Lett., 2018, 4, (2), pp 209216.CrossRefGoogle Scholar
Tuna, T., Ovur, S.E., Gokbel, E. and Kumbasar, T. Folly: A self foldable and self deployable autonomous quadcopter, In 2018 6th International Conference on Control Engineering & Information Technology (CEIT), pp 1–6. IEEE, 2018.CrossRefGoogle Scholar
Chanzy, Q. and Keane, A.J. Analysis and experimental validation of morphing uav wings, Aeronaut. J., 2018, 122, (1249), pp 390408.CrossRefGoogle Scholar
Derrouaoui, S.H., Bouzid, Y. and Guiatni, M. Towards a new design with generic modeling and adaptive control of a transformable quadrotor, Aeronaut. J., 2021, 125, (1294), pp 131.CrossRefGoogle Scholar
Derrouaoui, S.H., Guiatni, M., Bouzid, Y., Dib, I. and Moudjari, N. Dynamic modeling of a transformable quadrotor, In International Conference on Unmanned Aircraft Systems (ICUAS), pp 17141719. IEEE, 2020.CrossRefGoogle Scholar
Bhat, S.P. and Bernstein, D. Finite-time stability of continuous autonomous systems. Cont. Optimiz., 2000, 38, (3), pp 751766.CrossRefGoogle Scholar
Bhat, S.P. and Bernstein, D. Continuous finite-time stabilization of the translational and rotational double integrators, Automat. Cont., 1998, 43, (5), pp 678682.Google Scholar