Hostname: page-component-cb9f654ff-hqlzj Total loading time: 0 Render date: 2025-08-23T07:43:42.682Z Has data issue: false hasContentIssue false
  • English
  • Français

Robust Multimode Flight Framework Based on Sliding Mode Control for a Rotary UAV

Published online by Cambridge University Press:  24 July 2020

Abraham Villanueva ,
Luis F. Luque-Vega Open the ORCID record for Luis F. Luque-Vega [Opens in a new window] ,
Luis E. González-Jiménez Open the ORCID record for Luis E. González-Jiménez [Opens in a new window]  and
Carlos A. Arellano-Muro
Abraham Villanueva
Affiliation:
CINVESTAV-IPN Unidad Guadalajara, Zapopan, Jalisco, Mexico. E-mails: abrahamvn@gmail.com, carellano@gdl.cinvestav.mx
Luis F. Luque-Vega
Affiliation:
Centro de Investigación, Innovación y Desarrollo Tecnológico CIIDETEC-UVM, Universidad del Valle de México, Tlaquepaque, Jalisco 45601, Mexico. E-mail: luis.luque@uvmnet.edu
Luis E. González-Jiménez
Affiliation:
Department of Electronics, Systems and Informatics, ITESO - The Jesuit University of Guadalajara, Tlaquepaque, Jalisco, Mexico.
Carlos A. Arellano-Muro
Affiliation:
CINVESTAV-IPN Unidad Guadalajara, Zapopan, Jalisco, Mexico. E-mails: abrahamvn@gmail.com, carellano@gdl.cinvestav.mx
Get access Rights & Permissions [Opens in a new window]

Summary

This work presents a multimode flight framework control scheme for a quadrotor based on the super twisting algorithm. The controller design stages for six flight control modes are presented. The stability proof for each flight mode is carried out by means of Lyapunov functions, while the stability analysis for the complete control scheme, when a transition from one flight mode to another occurs, is demonstrated using the switching nonlinear systems theory. The performance of the proposed framework is shown in a 3D simulation environment considering a forest fire detection task, which takes into account external disturbances.

Keywords

Sliding modesMultimode flight controlQuadrotorSwitching dynamics

Information

Type
Articles
Information
Robotica , Volume 39 , Issue 4 , April 2021 , pp. 699 - 717
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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.)

Article purchase

Temporarily unavailable

References

Castillo, P., Dzul, A. and Lozano, R., “Real-time stabilization and tracking of a four-rotor mini rotorcraft,” IEEE Trans. Cont. Sys. Tech. 4(12), 510–516 (2004).CrossRefGoogle Scholar
Derafa, L., Fridman, L., Benallegue, A. and Ouldali, A., “Super Twisting Control Algorithm for the Four Rotors Helicopter Attitude Tracking Problem,” Proceedings of the 11th International Workshop on Variable Structure Systems (VSS) (2010) pp. 62–67.Google Scholar
Rabhi, A., Chadli, M. and Pegard, C., “Robust Fuzzy Control for Stabilization of a Quadrotor,” Proceedings of the 15th International Conference on Advanced Robotics (ICAR) (2011) pp. 471–475.Google Scholar
Khebbache, H., Sait, B., Yacef, F. and Soukkou, Y., “Robust stabilization of a quadrotor aerial vehicle in presence of actuator faults,” IJITCA 2(2), 1–13 (2012).CrossRefGoogle Scholar
Madani, T. and Benallegue, A., “Backstepping Control with Exact 2-Sliding Mode Estimation for a Quadrotor Unmanned Aerial Vehicle,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems 2007 (2007) pp. 141–146.Google Scholar
Benallegue, A., Mokhtari, A. and Fridman, L., “Feedback Linearization and High Order Sliding Mode Observer for a Quadrotor UAV,” Proceedings of the International Workshop on Variable Structure Systems (2006) pp. 365–372.Google Scholar
Madani, T. and Benallegue, A., “Sliding Mode Observer and Backstepping Control for a Quadrotor Unmanned Aerial Vehicles,” Proceedings of the American Control Conference ’07 (2007) pp. 5887–5892.Google Scholar
Stevanovic, S., Kasac, J. and Stepanic, J., “Robust Tracking Control of a Quadrotor Helicopter without Velocity Measurement,” 23rd International DAAAM Symposium (2012) pp. 595–600.Google Scholar
Islam, S., Liu, P. and Saddik, A., “Nonlinear robust adaptive sliding mode control design for miniature unmanned multirotor aerial vehicle,” Int. J. Control Autom. Syst. 15(10), 1–8 (2017).CrossRefGoogle Scholar
Zhang, J., Li, Q., Cheng, N. and Liang, B., “Non-linear flight control for unmanned aerial vehicles using adaptive backstepping based on invariant manifolds,” J. Aerospace Eng. 1(227), 33–44 (2013).Google Scholar
Basri, M., “Trajectory tracking control of autonomous quadrotor helicopter using robust neural adaptive backstepping approach,” J. Aerospace Eng. 21(2), 1–15 (2018).Google Scholar
Razmi, H. and Afshinfar, S., “Neural network-based adaptive sliding mode control design for position and attitude control of a quadrotor UAV,” Aerospace Sci. Tech. 91, 12–27 (2019).CrossRefGoogle Scholar
Zhang, C., Zhou, X., Zhao, H., Dai, A. and Zhou, H., “Three-Dimensional Fuzzy Control of Mini Quadrotor UAV Trajectory Tracking Under Impact of Wind Disturbance”, Proceedings of the 2016 International Conference on Advanced Mechatronic Systems (2016) pp. 372–377.Google Scholar
Zou, Y. and Meng, Z., “Immersion and invariance-based adaptive controller for quadrotor systems,” IEEE Trans. Syst. Man Cybern. Syst. 49(11), 2288–2297 (2018).CrossRefGoogle Scholar
Jiang, T., Song, T. and Lin, D., “Integral sliding mode based control for quadrotors with disturbances: Simulations and experiments,” Int. J. Control Autom. Syst. 17(8), 1987–1998 (2019).CrossRefGoogle Scholar
Redrovan, D. and Kim, D., “Multiple Quadrotors Flight Formation Control Based on Sliding Mode Control and Trajectory Tracking,” Proceedings of the 2018 International Conference on Electronics, Information, and Communication (ICEIC) (2018) pp. 1–6.Google Scholar
http://copter.ardupilot.com/wiki/flight-modes.Google Scholar
Bo, L. and Ping, L., “A Stateflow Based Simulation of UAV Multi-mode Flight Control,” Proceedings of the 8th World Congress on Intelligent Control and Automation (2010) pp. 3347–3352.Google Scholar
Hongzhe, X., Jim, H. and Yaoming, Z., “Design of Multi-mode Flight Control System for Unmanned Helicopter,” Proceedings of the 30th Chinese Control Conference (2011) pp. 3660–3663.Google Scholar
Boskovic, J. and Mehra, R., “Multi-mode Switching in Flight Control,” Proceedings of the The 19th Digital Avionics Systems Conference (2000) pp. 6F2/1–6F2/8.Google Scholar
Villanueva, A., Castillo-Toledo, B., Bayro-Corrochano, E., Luque-Vega, L. F. and Gonzalez-Jimenez, L. E., “Multi-mode Flight Sliding Mode Control System for a Quadrotor,” Proceedings of the 2015 International Conference on Unmanned Aircraft Systems (ICUAS), Denver, CO (2015) pp. 861–870.Google Scholar
Bouabdallah, S., Murrieri, P. and Siegwart, R., “Design and Control of an Indoor Micro Quadrotor,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’04) (2004) pp. 4393–4398.Google Scholar
Levant, A., “Universal single-input-single-output (SISO) sliding-mode controllers with finite-time convergence,” IEEE Trans. Aut. Cont. 9(46), 1447–1451 (2001).CrossRefGoogle Scholar
Gonzalez-Jimenez, L., Loukianov, A. and Bayro-Corrochano, E., “Fully Nested Super-Twisting Algorithm for Uncertain Robotic Manipulators,” Proceedings of the 2011 IEEE International Conference on Robotics and Automation (2011) pp. 5807–5812.Google Scholar
Moreno, J. and Osorio, M., “A Lyapunov Approach to Second-Order Sliding Mode Controllers and Observers,” Proceedings of the 47th IEEE Conference on Decision and Control (2008) pp. 2856–2861.Google Scholar
Moulay, E., Bourdaisa, R. and Perruquetti, W., “Stabilization of nonlinear switched systems using control Lyapunov functions,” Nonlinear Anal. Hybrid Syst. 4(1), 482–490 (2007).CrossRefGoogle Scholar
Murray Wonham, W. and Cai, Kai, Supervisory Control of Discrete-Event Systems, 1st edn. (Springer International Publishing, Switzerland, 2019).Google Scholar