Abstract—This paper proposes the use of the Gbest-Guided Artificial Bee Colony (GABC) algorithm to solve an online optimization problem for the leaderless distributed formation control of hexarotor Unmanned Aerial Vehicles (UAVs). The GABC is employed to optimize a cost function for each agent while ensuring the convergence of the fleet to the target position and averting both obstacles and collisions with other UAVs. The GABC algorithm has been shown to be competitive with some other conventional biological-inspired algorithms such as the Particle Swarm Optimization (PSO). Fault-Tolerant Control (FTC) methods are presented and tested on several scenarios, particularly we considered the cases of loss of agents and actuator faults in the fleet. Results show the success of the proposed FTC methods to minimize the faults effect on the formation final goal.
Similar content being viewed by others
Notes
The video of the simulation is shown at: https://youtu.be/sMTEfGGa58k
REFERENCES
Shakhatreh, H., Sawalmeh, A., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., Othman, N., Khreishah, A., and Guizani, M., Unmanned Aerial Vehicles (UAVs): A survey on civil applications and key research challenges, IEEE Access 7, 2019, pp. 48572−48634.
Sreenath, K. and Kumar, V., Dynamics, control and planning for cooperative manipulation of payloads suspended by cables from multiple quadrotor robots, in Robotics: Science and Systems, Berlin, 2013.
Franchi, A., Secchi, C., Ryll, M., Bulthoff, H., and Giordano, P., Shared control: Balancing autonomy and human assistance with a group of quadrotor UAVs, IEEE Robot. Autom. Mag., 2012, vol. 19, no. 3, pp. 57–68.
Ritz, R. and D’Andrea, R., Carrying a flexible payload with multiple flying vehicles, in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan, 3-7 November 2013, pp. 3465–3471.
Jiang, Q. and Kumar, V., The inverse kinematics of cooperative transport with multiple aerial robots, IEEE Trans. Robot., 2013, vol. 29, no. 1, pp. 136–145.
Kushleyev, A., Kumar, V., and Mellinger, D., Towards a swarm of agile micro quadrotors, Proc. Robot., Sci. Syst., Sydney, NSW, Australia, 2012.
Michael, N., Fink, J., and Kumar, V., 2009, Cooperative manipulation and transportation with aerial robots, Proc. Robot., Sci. Syst., Seattle, WA, USA, 2009.
Dames, P. and Kumar, V., Autonomous localization of an unknown number of targets without data association using teams of mobile sensors, IEEE Trans. Autom. Sci. Eng., 2015, vol. 12, no. 3, pp. 850–864.
Saska, M. et al., Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance, Proc. Int. Conf. Unmanned Aircraft Syst. (ICUAS), Orlando, FL, USA, 27-30 May 2014, pp. 584–595.
Hou, Z. and Fantoni, I., Interactive leader–follower consensus of multiple quadrotors based on composite nonlinear feedback control, IEEE Transactions on Control Systems Technology, 2018, vol. 26, no. 5, pp. 1732–1743.
Vasarheyli, G., Viragh, Cs., Somorjai, G., Tarcai, N., Szorenyi, T., Nepusz, T., and Viscek, T., Outdoor flocking and formation flight with autonomous aerial robots, Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA, 14−18 September 2014.
Scollig, A., Augugliaro, F., Lupashin, S., and D’Andrea, R., Synchronizing the motion of a quadcopter to music, IEEE International Conference on Robotics and Automation, Anchorage, AK, USA, May 3-8 2010, pp. 3355−3360.
Kushleyev, A., Mellinger, D., Powers, C., and Kumar, V., Towards a swarm of agile micro quadrotors, Autonomous Robots, 2013, vol. 35, no. 4, pp. 287–300.
Reynolds, C., Flocks, herds, and schools: A distributed behavioral model, Proc. of the 14th Annual Conference on Computer Graphics and Interactive Techniques, 1987, pp. 25–34.
Olfati-Saber, R., Flocking for multi-agent dynamic systems: algorithms and theory, IEEE Transactions on Automatic Control, 2007, vol. 51, pp. 863–868.
Antonelli, G., Arrichiello, F., and Chiaverini, S., Flocking for multirobot systems via the nullspace based behavioral control, Swarm Intelligence, 2010, vol. 4, no. 37.
Bellingham, J., Tillerson, M., Alighanbari, M., and How, J., Cooperative path planning for multiple UAVs in dynamic and uncertain environments, Proc. IEEE Conference on Decision and Control, Las Vegas, NV, USA, 2002.
Richards, A. and How, J., Aircraft trajectory planning with collision avoidance using mixed integer linear programming, Proc. IEEE American Control Conference, Anchorage, AK, USA, 2002.
Tanner, H., Jadbabaie, A., and Pappas, G., Flocking in fixed and switching networks, IEEE Transactions on Automatic Control, 2007, vol. 52, no. 5, pp. 863–868.
Bakule, L., Decentralized control: An overview, Annual Reviews in Control, 2008, vol. 32, no. 1, pp. 87−98.
Jovanovic, M., Modeling, analysis, and control of spatially distributed systems, PhD Thesis, University of California, Santa Barbara, 2004.
Brunet, L., Consensus-based auction approaches for decentralized task assignment, AIAA Guidance, Navigation and Control Conference and Exhibit, Honolulu, Hawaii, 2008.
Quin, J., and Yu, C., Cluster consensus control of generic linear multi-agent systems under directed topology with acyclic partition, Automatica, 2013, vol. 49, no. 9, pp. 2898–2905.
Belkadi, A., Ciarletta, L., and Theilliol, D., UAVs fleet control design using distributed particle swarm optimization: A leaderless approach, International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA, USA, 2016.
Belkadi, A., Abaunza, H., Ciarletta, L., Castillo, P., and Theilliol, D., Distributed path planning for controlling a fleet of UAVs: Application to a team of quadrotors, IFAC-PapersOnline, 2017, vol. 50, no. 1, pp. 15983–15989.
Abdmouleh, Z., Gastli, A., Ben-Brahim, L., Haouari, M., and Al-Emadi, N., Review of optimization techniques applied for the integration of distributed generation from renewable energy sources, Renewable Energy, 2017, vol. 113, pp. 266–280.
Karaboga, D. and Basturk, B., Artificial Bee Colony (ABC) optimization algorithm for solving constrained optimization problems, Foundations of Fuzzy Logic and Soft Computing, Berlin: Springer-Verlag, 2007, pp. 789–798.
Bhattacharjee, P., Rakshit, P., Goswami, I., Konar, A., and Nagar, A., Muti-robot path-planning using artificial bee colony optimization algorithm, Proc. World Congress on Nature and Biologically Inspired Computing, Salamanca, Spain, 2011.
Soyinka, O. and Duan, H., Satellite formation keeping via chaotic artificial bee colony, Aircr. Eng. Aerosp. Technol., 2017, vol. 89, no. 2, pp. 246–256.
Zhou, B., Wang, W., and Ye, H., Cooperative control for consensus of multi-agent systems with actuator faults, Computers & Electrical Engineering, 2014, vol. 40, no. 7, pp. 2154–2166.
Saska, M., Krajnik., T., Vonasek, V., Kasl, Z., Spurny, V., and Preucil, L., Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups, Journal of Intelligent & Robotic Systems, 2014, vol. 73, no. 1, pp. 603–622.
Belkadi, A., Conception de commande tolerante aux defauts pour les systemes multi-agents: application au vol en formation d’une flotte de vehicules autonomes aeriens, Ph.D. dissertation, University of Lorraine, France, 2017.
Diestel, R., Graph Theory. Graduate Texts in Mathematics, Heidelberg: SpringerVerlag, 2005, third edition.
Sanahuja, G., Castillo, P., and Sanchez, A., Stabilization of n integrators in cascade with bounded input with experimental application to a VTOL laboratory system, International Journal of Robust and Nonlinear Control, 2010, vol. 20, no. 10, pp. 1129–1139.
Lalitha, M., Reddy, N., and Reddy, V., Optimal DG placement for maximum loss reduction in radial distribution system using ABC algorithm, Int. J. Rev. Comput, 2010, vol. 3, pp. 44–52.
Zhu, G. and Knowg, S., Gbest-guided artificial bee colony algorithm for numerical function optimization, Applied Mathematics and Computation, 2010, vol. 217, no. 7, pp. 3166–3173.
Saied, M., Knaiber, M., Mazeh, H., Shraim, H., and Francis, C., BFA fuzzy logic based control allocation for fault-tolerant control of multirotor UAVs, The Aeronautical Journal, 2019, vol. 123, pp. 1356–1373.
Mazeh, H., Saied, M., Shraim, H., and Francis, C., Fault-tolerant control of an hexarotor unmanned aerial vehicle applying outdoor tests and experiments. IFAC-PapersOnline, 2018, vol. 51, no. 22, pp. 312–317.
ACKNOWLEDGEMENTS
This work received support from the Lebanese University Research Support Program.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Slim, M., Saied, M., Mazeh, H. et al. Fault-Tolerant Control Design for Multirotor UAVs Formation Flight. Gyroscopy Navig. 12, 166–177 (2021). https://doi.org/10.1134/S2075108721020061
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S2075108721020061