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Active versus passive fault-tolerant control of a redundant multirotor UAV

Published online by Cambridge University Press:  26 November 2019

M. Saied Open the ORCID record for M. Saied [Opens in a new window] ,
B. Lussier ,
I. Fantoni ,
H. Shraim  and
C. Francis
M. Saied*
Affiliation:
Sorbonne Universités, Université de Technologie de Compiègne, CNRS, UMR 7253 Heudiasyc, Compiègne, France Lebanese University, Faculty of Engineering, Scientific Research Center in Engineering, Beirut, Lebanon
B. Lussier
Affiliation:
Sorbonne Universités, Université de Technologie de Compiègne, CNRS, UMR 7253 Heudiasyc, Compiègne, France
I. Fantoni
Affiliation:
Sorbonne Universités, Université de Technologie de Compiègne, CNRS, UMR 7253 Heudiasyc, Compiègne, France LS2N UMR CNRS 6004, Nantes, France
H. Shraim
Affiliation:
Lebanese University, Faculty of Engineering, Scientific Research Center in Engineering, Beirut, Lebanon
C. Francis
Affiliation:
Lebanese University, Faculty of Engineering, Scientific Research Center in Engineering, Beirut, Lebanon
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Abstract

This paper considers actuator redundancy management for a redundant multirotor Unmanned Aerial Vehicle (UAV) under actuators failures. Different approaches are proposed: using robust control (passive fault tolerance), and reconfigurable control (active fault tolerance). The robust controller is designed using high-order super-twisting sliding mode techniques, and handles the failures without requiring information from a Fault Detection scheme. The Active Fault-Tolerant Control (AFTC) is achieved through redistributing the control signals among the healthy actuators using reconfigurable multiplexing and pseudo-inverse control allocation. The Fault Detection and Isolation problem is also considered by proposing model-based and model-free modules. The proposed techniques are all implemented on a coaxial octorotor UAV. Different experiments with different scenarios were conducted for the validation of the proposed strategies. Finally, advantages, disadvantages, application considerations and limitations of each method are examined through quantitative and qualitative studies.

Keywords

Fault Tolerant ControlFault Diagnosisunmanned aerial vehicles
Type
Research Article
Information
The Aeronautical Journal , Volume 124 , Issue 1273 , March 2020 , pp. 385 - 408
Copyright
© Royal Aeronautical Society 2019 

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References

REFERENCES

Mahjri, I., Dhraie, A. and Belghith, A. A Review on Collision Avoidance Systems for Unmanned Aerial Vehicles, International Workshop on Communication Technologies for Vehicles, 2015.CrossRefGoogle Scholar
Chamseddine, A., Zhang, Y., Rabbath, C.A., Join, C. and Theilliol, D. Flatness-based trajectory planning/replanning for a Quadrotor unmanned aerial vehicle, IEEE Transactions on Aerospace and Electronic Systems, 2012, 48, (4), pp 2832–2848.CrossRefGoogle Scholar
Avram, R., Zhang, X. and Muse, J. Nonlinear adaptive fault-tolerant quadrotor altitude and attitude tracking with multiple actuator faults, IEEE Transactions on Control Systems Technology, 2018, 26, (2), pp 701–707.CrossRefGoogle Scholar
Avram, R., Zhang, X. and Muse, J. Quadrotor actuator fault diagnosis and accommodation using nonlinear adaptive estimators, IEEE Transactions on Control Systems Technology, 2017, 25, (6), pp 2219–2226.CrossRefGoogle Scholar
Chen, F., Jiang, R., Zhang, K., Jiang, B. and Tao, G. Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV, IEEE Transactions on Industrial Electronics, 2016, 63, (8), pp 5044–5056.Google Scholar
Mueller, M. and D’Andrea, R. Relaxed hover solutions for multicopters: application to algorithmic redundancy and novel vehicles, The International Journal of Robotics Research, 2016, 35, (8), pp 873–889.CrossRefGoogle Scholar
Alwi, H. and Edwards, C. Sliding mode fault-tolerant control of an octorotor using linear parameter varying-based schemes, IET Control Theory and Applications, 2015, 9, (4), pp 618–636.CrossRefGoogle Scholar
Zeghlache, S., Saigaa, D. and Kara, K. Fault tolerant control based on neural network interval type-2 fuzzy sliding mode controller for octorotor UAV, Frontiers of Computer Science, 2016, 10, (4), pp 657–672.CrossRefGoogle Scholar
Alwi, H., Hamayun, M. and Edwards, C. An integral sliding mode fault tolerant control scheme for an octorotor using xed control allocation, 13th International Workshop on Variable Structure Systems (VSS), 2014, pp 1–6.CrossRefGoogle Scholar
Marks, A., Whidborne, J.F. and Yamamoto, I. Control allocation for fault tolerant control of a VTOL octorotor, UKACC International Conference on Control, 2012, pp 357–362.CrossRefGoogle Scholar
Saied, M., Lussier, B., Fantoni, I., Francis, C. and Shraim, H. Fault tolerant control for multiple successive failures in an octorotor: architecture and experiments, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015, pp 40–45.CrossRefGoogle Scholar
Saied, M., Lussier, B., Fantoni, I., Shraim, H. and Francis, C. Passive fault tolerant control of an octorotor using super-twisting algorithm: theory and experiments, 3rd Conference on Control and Fault-Tolerant Systems (SysTol), 2016, pp 361–366.CrossRefGoogle Scholar
Saied, M., Lussier, B., Fantoni, I., Francis, C., Shraim, H. and Sanahuja, G. Fault diagnosis and fault-tolerant control strategy for rotor failure in an octorotor, International Conference on Robotics and Automation (ICRA), 2015, pp 5266–5271.CrossRefGoogle Scholar
Sontag, E.D. Kalman’s controllability rank condition: from linear to nonlinear, Mathematical System Theory, Springer Berlin Heidelberg, 1991, pp 453–462.CrossRefGoogle Scholar
Saied, M., Shraim, H., Lussier, B., Fantoni, I. and Francis, C. Local controllability and attitude stabilization of multirotor UAVs: Validation on a coaxial octorotor, Robotics and Autonomous Systems, 2017, 91, pp 128–138.CrossRefGoogle Scholar
Zhang, Y. and Jiang, J. Bibliographical review on reconfigurable fault tolerant control systems, Annual Reviews in Control, 2008, 32, pp 229–252.CrossRefGoogle Scholar
Davila, J., Fridman, L. and Levant, A. Second-order sliding-mode observer for mechanical systems, IEEE Transactions on Automatic Control, 2005, 50, (11), pp 1785–1789.CrossRefGoogle Scholar
Vapnik, V. The Nature of Statistical Learning Theory, Springer, 2000.CrossRefGoogle Scholar
Sari, A.H. Data-Driven Design of Fault Diagnosis Systems: Nonlinear Multimode Processes, Springer Vieweg, 2013.Google Scholar
Boskovic, J. and Mehra, R. Control allocation in overactuated aircraft under position and rate limiting, American Control Conference (ACC), 2002, pp 791–796.Google Scholar
Benosman, M. Passive Fault Tolerant Control, Robust Control, Theory and Applications, InTech, 2011.Google Scholar
Edwards, C. and Spurgeon, S. Sliding Mode Control: Theory and Applications, Taylor & Francis, 1998.CrossRefGoogle Scholar
Derafa, L., Benallegue, A. and Fridman, L. Super twisting control algorithm for the attitude tracking of a four rotors UAV, Journal of the Franklin Institute, 2012, 349, (2), pp 685–699.CrossRefGoogle Scholar