Abstract
This chapter studies control strategies for load carrying drones. Load carrying drones not only have to fly in a cooperative way, but also are mechanically interconnected. Due to these characteristics, the control problem is an interesting and challenging issue to deal with. Throughout this chapter, a dynamic model based on first principle is developed. To that end, it is proposed to model this system as a ball and beam system lifted by two drones. Afterwards, different control techniques are implemented and compared by simulations. Specifically, linear-quadratic regulator (LQR) and model predictive control (MPC) are studied. Both control techniques belong to the optimal control methodology. This comparison is interesting since LQR permits to perform an optimal control law with short execution times, while MPC deals with physical constraints and predictions, being the execution time and the physical constraints important issues to handle in this kind of systems. Finally, simulation results and open issues are discussed.
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References
P. McBride, B. Orwell, The application of unmanned aircraft systems in domestic surveillance operations. J. Air Law Comm. Summer 74(3), 627–628 (2009)
D. Zorbas, T. Razafindralambo, D.P. Luigi, F. Guerriero, Energy efficient mobile target tracking using flying drones. Proc. Comput. Sci. 19, 80–87 (2013)
H. Chen, X. Wang, Y. Li, A survey of autonomous control for uav, in International Conference on Artificial Intelligence and Computational Intelligence, vol. 2, 2009, pp. 267–271
G. Hoffmann, H. Huang, S. Waslander, C. Tomlin, Quadrotor helicopter flight dynamics and control: theory and experiment, in The AIAA Guidance, Navigation, and Control Conference, 2007
S. Bouabdallah, M. Becker, R. Siegwart, Autonomous miniature flying robots: coming soon-research, development, and results. IEEE Robot. Autom. Mag. 14(3), 88–98 (2007)
K. Alexis, G. Nikolakopoulos, A. Tzes, Switching model predictive attitude control for a quadrotor helicopter subject to atmospheric disturbances. Control Eng. Pract. 19, 1195–1207 (2011)
S. Bouabdallah, A. Noth, R. Siegwart, PID-LQ control techniques applied to an indoor micro quadrotor, in The IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004, pp. 2451–2456
S. Waslander, G. Hoffmann, J. Jang, C. Tomlin, Multi-agent quadrotor test bed control design: integral sliding mode vs. reinforcement learning, in The IEEE/RSJ International Conference on Intelligent Robotics and Systems, 2005, pp. 468–473
G.V. Raffo, M.G. Ortega, F.R. Rubio, An integral predictive/nonlinear \(\fancyscript {H}_{\infty }\) control structure for a quadrotor helicopter. Automatica 46, 29–39 (2010)
S. Bouabdallah, Design and control of quadrotors with application to autonomous flying. Ph.D. dissertation, EPFL STI School of Engineering, Lausanne, Switzerland, 2007
E. Camacho, C. Bordons, Model Predictive Control (Springer, London, 2004)
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Rubio, A.A., Seuret, A., Ariba, Y., Mannisi, A. (2016). Optimal Control Strategies for Load Carrying Drones. In: Seuret, A., Hetel, L., Daafouz, J., Johansson, K. (eds) Delays and Networked Control Systems . Advances in Delays and Dynamics, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-32372-5_11
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DOI: https://doi.org/10.1007/978-3-319-32372-5_11
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