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Constrained generalized predictive control for obstacle avoidance in a quadcopter

Published online by Cambridge University Press:  06 June 2018

José Luis Mendoza-Soto ,
Luis Alvarez-Icaza  and
H. Rodríguez-Cortés Open the ORCID record for H. Rodríguez-Cortés [Opens in a new window]
José Luis Mendoza-Soto*
Affiliation:
División de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad Nacional Autónoma de México, Av. Universidad 3000, Ciudad Universitaria, Coyoacán, Ciudad de México 04510, México
Luis Alvarez-Icaza
Affiliation:
Instituto de Ingeniería, Universidad Nacional Autónoma de México, Av. Universidad 3000, Ciudad Universitaria, Coyoacán, Ciudad de México 04510, México. E-mail: alvar@pumas.iingen.unam.mx
H. Rodríguez-Cortés
Affiliation:
Sección de Mecatrónica, Departamento de Ingeniería Eléctrica, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, Gustavo A. Madero, Ciudad de México 07360, México. E-mail: hrodriguez@cinvestav.mx
*
*Corresponding author. E-mail: eemsj03@yahoo.com.mx
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Summary

This work proposes a strategy for position control and obstacle avoidance in a quadcopter based on constrained generalized predictive control and geometric attitude control. The approach allows real-time trajectory tracking using optimal control actions and avoids collisions with static obstacles whose position is known. An experimental validation of the proposed controller is presented.

Keywords

Generalized predictive controlQuadcopterUnmanned aerial vehicleObstacle avoidance
Type
Articles
Information
Robotica , Volume 36 , Issue 9 , September 2018 , pp. 1363 - 1385
Copyright
Copyright © Cambridge University Press 2018 

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References

1. IBM Corp. 1987, 2015. IBM ILOG CPLEX Optimization Studio Getting Started with CPLEX, Version 12 Release 6. IBM, USA (2015).Google Scholar
2. Abdolhosseini, M., Zhang, Y. M. and Rabbath, C. A., “An efficient model predictive control scheme for an unmanned quadrotor helicopter,” J. Intell. Robot. Syst. 70 (1–4), 27–38 (2013).Google Scholar
3. Alexis, K., Papachristos, C., Siegwart, R. and Tzes, A., “Robust model predictive flight control of unmanned rotorcrafts,” J. Intell. Robot. Syst. 81 (3–4), 443–469 (2016).Google Scholar
4. Bangura, M. and Mahony, R., “Real-time model predictive control for quadrotors,” IFAC Proc. Vol., 47 (3), 11773–11780 (2014) 19th IFAC World Congress.Google Scholar
5. Bemporad, A., Pascucci, C. A. and Rocchi, C., “Hierarchical and hybrid model predictive control of quadcopter air vehicles,” IFAC Proc. Vol. 42 (17), 14–19 (2009) 3rd IFAC Conference on Analysis and Design of Hybrid Systems.Google Scholar
6. Bemporad, A. and Rocchi, C., “Decentralized Linear Time-Varying Model Predictive Control of a Formation of Unmanned Aerial Vehicles,” Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference (Dec. 2011) pp. 7488–7493.Google Scholar
7. Camacho, E. F. and Bordons, C., Model Predictive Control (Springer-Verlag, Great Britain, 2004).Google Scholar
8. Engelhardt, T., Konrad, T., Schafer, B. and Abel, D., “Flatness-Based Control for a Quadrotor Camera Helicopter Using Model Predictive Control Trajectory Generation,” Proceedings of the 24th Mediterranean Conference on Control and Automation (MED), Athens, Greece (Jun. 21–24, 2016) pp. 852–859.Google Scholar
9. Lee, T., Leok, M. and McClamroch, N. H., “Geometric Tracking Control of a Quadrotor UAV on SE(3),” Proceedings of the 49th IEEE Conference on Decision and Control (CDC) (Dec. 2010) pp. 5420–5425.Google Scholar
10. Lee, T., Leok, M. and McClamroch, N. H., “Nonlinear robust tracking control of a quadrotor UAV on SE(3),” Asian J. Control 15 (2), 391–408 (2013).Google Scholar
11. Liu, C., Tang, S., Yang, S. and Li, Y., “Generalized Predictive Control with Dynamic Compensation for Quadrotor Attitude Stabilization,” Proceedings of the 33rd Chinese Control Conference (Jul. 2014) pp. 7709–7714.Google Scholar
12. Maciejowski, J. M., Predictive Control with Constraints (Pearson Education Limited, Prentice Hall, London, 2002).Google Scholar
13. Mellinger, D., Kushleyev, A. and Kumar, V., “Mixed-Integer Quadratic Program Trajectory Generation for Heterogeneous Quadrotor Teams,” Proceedings of the IEEE International Conference on Robotics and Automation (May 2012) pp. 477–483.Google Scholar
14. Mueller, M. W. and D'Andrea, R., “A Model Predictive Controller for Quadrocopter State Interception,” Proceedings of the European Control Conference (ECC) (Jul. 2013) pp. 1383–1389.Google Scholar
15. Neunert, M., de Crousaz, C., Furrer, F., Kamel, M., Farshidian, F., Siegwart, R. and Buchli, J., “Fast Nonlinear Model Predictive Control for Unified Trajectory Optimization and Tracking,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (May 2016) pp. 1398–1404.Google Scholar
16. Richards, A., Schouwenaars, T., How, J. P. and Feron, E., “Spacecraft trajectory planning with avoidance constraints using mixed-integer linear programming,” J. Guid., Control, Dyn. 25, 755–764 (2002).Google Scholar
17. Rochefort, Y., Bertrand, S., Piet-Lahanier, H., Beauvois, D. and Dumur, D., “Cooperative nonlinear model predictive control for flocks of vehicles,” IFAC Proc. Vol. 45 (1), 169–174 (2012) 1st IFAC Workshop on Embedded Guidance, Navigation and Control in Aerospace.Google Scholar
18. Schouwenaars, T., Feron, E. and How, J., “Multi-Vehicle Path Planning for Non-Line of Sight Communication,” Proceedings of the American Control Conference (Jun. 2006) p. 6.Google Scholar
19. Schouwenaars, T., De Moor, B., Feron, E. and How, J., “Mixed Integer Programming for Multi-Vehicle Path Planning,” Proceedings of the European Control Conference (ECC) (Sep. 2001) pp. 2603–2608.Google Scholar
20. Tlatelpa-Osorio, Y. E., Corona-Sánchez, J. J. and Rodríguez-Cortés, H., “Quadrotor Control Based on an Estimator of External Forces and Moments,” Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA, USA (Jun. 7–10, 2016) pp. 957–963.Google Scholar
21. Vlantis, P., Marantos, P., Bechlioulis, C. P. and Kyriakopoulos, K. J., “Quadrotor Landing on an Inclined Platform of a Moving Ground Vehicle,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (May 2015) pp. 2202–2207.Google Scholar
22. Zulu, A. and John, S., “A review of control algorithms for autonomous quadrotors,” Open J. Appl. Sci. 4, 547–556 (2014).Google Scholar