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Cascaded control for balancing an inverted pendulum on a flying quadrotor

Published online by Cambridge University Press:  09 February 2016

Chao Zhang ,
Huosheng Hu ,
Dongbing Gu  and
Jing Wang
Chao Zhang*
Affiliation:
Engineering Research Institute of USTB, University of Science and Technology Beijing, Beijing, China. E-mail: [email protected] Department of Computer Science and Electronic Engineering, University of Essex, Colchester, UK. E-mails: [email protected], [email protected]
Huosheng Hu
Affiliation:
Department of Computer Science and Electronic Engineering, University of Essex, Colchester, UK. E-mails: [email protected], [email protected]
Dongbing Gu
Affiliation:
Department of Computer Science and Electronic Engineering, University of Essex, Colchester, UK. E-mails: [email protected], [email protected]
Jing Wang
Affiliation:
Engineering Research Institute of USTB, University of Science and Technology Beijing, Beijing, China. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper is focused on the flying inverted pendulum problem, i.e., how to balance a pendulum on a flying quadrotor. After analyzing the system dynamics, a three loop cascade control strategy is proposed based on active disturbance rejection control (ADRC). Both the pendulum balancing and the trajectory tracking of the flying quadrotor are implemented by using the proposed control strategy. A simulation platform of 3D mechanical systems is deployed to verify the control performance and robustness of the proposed strategy, including a comparison with a Linear Quadratic Controller (LQR). Finally, a real quadrotor is flying with a pendulum to demonstrate the proposed method that can keep the system at equilibrium and show strong robustness against disturbances.

Keywords

Inverted pendulumMicro aerial vehiclesActive disturbance rejection controlCascade control
Type
Articles
Information
Robotica , Volume 35 , Issue 6 , June 2017 , pp. 1263 - 1279
Copyright
Copyright © Cambridge University Press 2016 

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References

1. Boubaker, O., “The inverted pendulum benchmark in nonlinear control theory: a survey,” Int. J. Adv. Robot. Sy. 10, 233–242 (2013).Google Scholar
2. Grasser, F., D'Arrigo, A., Colombi, S. and Rufer, A. C., “Joe: A mobile, inverted pendulum,” IEEE Trans. Indust. Electron. 49 (1), 107–114 (2002).Google Scholar
3. Wang, J.-J., “Simulation studies of inverted pendulum based on PID controllers,” Simul. Modelling Pract. Theory 19 (1), 440–449 (2011).Google Scholar
4. Jung, S., Cho, H.-T. and Hsia, T. C., “Neural network control for position tracking of a two-axis inverted pendulum system: Experimental studies,” IEEE Trans. Neural Netw. 18 (4), 1042–1048 (2007).Google Scholar
5. Bloch, A. M., Leonard, N. E. and Marsden, J. E., “Controlled lagrangians and the stabilization of mechanical systems. I. The first matching theorem,” IEEE Trans. Autom.Control 45 (12), 2253–2270 (2000).CrossRefGoogle Scholar
6. Cai, G., Dias, J. and Seneviratne, L., “A survey of small-scale unmanned aerial vehicles: Recent advances and future development trends,” Unmanned Syst. 2 (02), 175–199 (2014).Google Scholar
7. How, J. P., Fraser, C., Kulling, K. C., Bertuccelli, L. F., Toupet, O., Brunet, L., Bachrach, A. and Roy, N., “Increasing autonomy of uavs,” Robot. Autom. Mag. IEEE 16 (2), 43–51 (2009).Google Scholar
8. Lupashin, S., Hehn, M., Mueller, M. W., Schoellig, A. P., Sherback, M. and DAndrea, R., “A platform for aerial robotics research and demonstration: The flying machine arena,” Mechatronics 24 (1), 41–54 (2014).Google Scholar
9. Michael, N., Mellinger, D., Lindsey, Q. and Kumar, V., “The grasp multiple micro-uav testbed,” Robot. Autom. Mag. IEEE 17 (3), 56–65 (2010).Google Scholar
10. Hehn, M. and D'Andrea, R., “A Flying Inverted Pendulum,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China (2011) pp. 763–770.Google Scholar
11. Figueroa, R., Faust, A., Cruz, P., Tapia, L. and Fierro, R., “Reinforcement Learning for Balancing a Flying Inverted Pendulum,” Proceedings of the 11th World Congress on Intelligent Control and Automation, IEEE. Shenyang, China (2014) pp. 1787–1793.Google Scholar
12. Raimundez, C., Camano, J. L. and Barreiro, A., “Stabilizing an Inverted Spherical Pendulum using a Scale Quad-Rotor,” Proceedings of the IEEE 4th Annual International Conference on Cyber Technology in Automation, Control and Intelligent Systems (CYBER), Hong Kong, China (2014) pp. 111–116.Google Scholar
13. Sandoval, J., Kelly, R. and Santibanez, V., “On the Controlled Lagrangian of an Inverted Pendulum on a Force-Driven Cart,” Proceedings of the Control Conference (ECC), 2015 European, IEEE. Linz, Austria (2015) pp. 992–997.Google Scholar
14. Abdessameud, A., Polushin, I. and Tayebi, A., “Motion coordination of thrust-propelled underactuated vehicles with intermittent and delayed communications,” Syst. Control Lett. 79, 15–22 (2015).Google Scholar
15. Guo, L. and Cao, S., “Anti-disturbance control theory for systems with multiple disturbances: A survey,” ISA Trans. 53 (4), 846–849 (2014).Google Scholar
16. Ohishi, K., Nakao, M., Ohnishi, K. and Miyachi, K., “Microprocessor-controlled dc motor for load-insensitive position servo system,” IEEE Trans. Indust. Electron. 1 (IE–34), 44–49 (1987).Google Scholar
17. Li, S. and Yang, J., “Robust autopilot design for bank-to-turn missiles using disturbance observers,” IEEE Trans. Aerosp. Electron. Syst. 49 (1), 558–579 (2013).Google Scholar
18. Xing, D., Su, J., Liu, Y. and Zhong, J., “Robust approach for humanoid joint control based on a disturbance observer,” Control Theory Appl. IET 5 (14), 1630–1636 (2011).Google Scholar
19. Tan, K. K., Lee, T. H., Dou, H. F., Chin, S. J. and Zhao, S., “Precision motion control with disturbance observer for pulsewidth-modulated-driven permanent-magnet linear motors,” IEEE Trans. Magn. 39 (3), 1813–1818 (2003).Google Scholar
20. Han, J., “From PID to active disturbance rejection control,” IEEE Trans. Indust. Electron. 56 (3), 900–906 (2009).Google Scholar
21. Ramirez-Neria, M., Sira-Ramirez, H., Garrido-Moctezuma, R. and Luviano-Juárez, A., “Linear active disturbance rejection control of underactuated systems: The case of the furuta pendulum,” ISA Trans. 53 (4), 920–928 (2014).Google Scholar
22. Zhang, C. and Zhu, J., “On Stabilization and Disturbance Rejection for the Inverted Pendulum,” Proceedings of the IEEE International Conference on Systems, Man and Cybernetics (SMC), San Diego, CA (2014) pp. 3750–3754.Google Scholar
23. Esteban, S., Gordillo, F. and Aracil, J., “Three-time scale singular perturbation control and stability analysis for an autonomous helicopter on a platform,” Int. J. Robust Nonlinear Control 23 (12), 1360–1392 (2013).CrossRefGoogle Scholar
24. Wood, G. D. and Kennedy, D. C., “Simulating mechanical systems in simulink with simmechanics,” Technical Report 91124v00, The Mathworks Report Inc., Natick, MA, (2003).Google Scholar
25. Gurdan, D., Stumpf, J., Achtelik, M., Doth, K.-M., Hirzinger, G. and Rus, D., “Energy-Efficient Autonomous Four-Rotor Flying Robot Controlled at 1 KHz,” Proceedings of the IEEE International Conference on Robotics and Automation, Roma, Italy (2007) pp. 361–366.Google Scholar
26. Kendoul, F., “Survey of advances in guidance, navigation and control of unmanned rotorcraft systems,” J. Field Robot. 29 (2), 315–378 (2012).Google Scholar
27. Gao, Z., “Scaling and Bandwidth-Parameterization Based Controller Tuning,” Proceedings of the American Control Conference, vol. 6 Denver, Colorado, USA (2006) pp. 4989–4996.Google Scholar
28. Sa, I. and Corke, P., “System Identification, Estimation and Control for a Cost Effective Open-Source Quadcopter,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Saint Paul, MN, USA (2012) pp. 2202–2209.Google Scholar
29. Nasir, A. N. K., Ahmad, M. A. and Rahmat, M. F., “Performance Comparison between LQR and PID Controllers for an Inverted Pendulum System,” Proceedings of the International Conference on Power Control and Optimization: Innovation in Power Control for Optimal Industry, AIP Publishing, vol. 1052 Chiangmai, Thailand (2008) pp. 124–128.Google Scholar