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A novel hybrid back-stepping and fuzzy logic control strategy for a quadcopter

Published online by Cambridge University Press:  03 August 2017

H. Shraim*
Affiliation:
Lebanese University, Faculty of Engineering III, Beirut, Lebanon
Y. Harkouss
Affiliation:
Lebanese University, Faculty of Engineering III, Beirut, Lebanon
H. Bazzi
Affiliation:
Lebanese University, Faculty of Engineering III, Beirut, Lebanon

Abstract

This article aims to present a novel control strategy for quadrotor helicopter. It is composed of three main parts constituting the system modelling, the integral back-stepping control, and fuzzy logic compensator. In the first part, a non-linear model is presented taking in consideration some non-linearities and variables that are usually neglected. In the second part, a controller based on the integral back-stepping algorithm has been developed for the system in order to make the system follows a desired path. However, due to complexity of paths and to the presence of unknown disturbances, a fuzzy logic compensator is added in parallel to the integral back-stepping controller to improve trajectory tracking in some critical conditions (high wind speed, mass variation, etc.). Simulation results have been presented to show the effectiveness of the proposed approach.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2017 

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References

REFERENCES

1. Fantoni, I. and Lozano, R. Nonlinear Control for Underactuated Mechanical Systems, Springer-Verlag, London, UK, 1995.Google Scholar
2. Castillo, P., Lozano, R. and Dzul, A.E. Modelling and control of mini-flying machines, Springer-Verlag, 2005, London, UK.Google Scholar
3. Raffo, G.V., Ortega, M.G. and Rubio, F.R. Backstepping/nonlinear H∞ control for path tracking of a quadrotor unmanned aerial vehicle, 2008 American Control Conference, 11–13 June 2008, Washington, DC, USCrossRefGoogle Scholar
4. Pounds, P., Mahony, R. and Corke, P. Modelling and control of a large quadrotor robot, Control Engineering Practice, 2010, 18, (7), pp 691-699.CrossRefGoogle Scholar
5. Kim, J.H., Kang, M.S. and Park, S. Accurate modeling and robust hovering control for a quadrotor VTOL aircraft, J of Intelligent and Robotic Systems, 2010, 57, (1–4), pp 9-26.CrossRefGoogle Scholar
6. Elsamanty, M., Khalifa, A., Fanni, M., Ramadan, A. and Abo-Ismail, A. Methodology for identifying quadrotor parameters, attitude estimation and control, Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM ’13), July 2013, Wollongong, Australia, pp 1343–1348.CrossRefGoogle Scholar
7. Kim, J., Kang, M.S. and Park, S. Accurate modeling and robust hovering control for a quad-rotor VTOL aircraft, J of Intelligent and Robotic Systems, 2010, 57, (1–4), pp 9-26.CrossRefGoogle Scholar
8. Mistler, V., Benallegue, A. and M'Sirdi, N.K. Exact linearization and noninteracting control of a 4 rotors helicopter via dynamic feedback, IEEE International Workshop on Robot and Human Interactive Communication, Bordeaux, France, 2001.Google Scholar
9. Mokhtari, A., Benallegue, A. and Orlov, Y. Exact linearization and sliding mode observer for a quadrotor unmanned aerial vehicle, Int J of Robotics and Automation, 2006, 21, (1), pp 39-49.CrossRefGoogle Scholar
10. Bouabdallah, S., Murrieri, P. and Siegwart, R. Design and control of an indoor micro quadrotor, Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004, New Orleans, Louisiana, US, pp 4393-4398.CrossRefGoogle Scholar
11. Ortega, M.G., Vargas, M., Vivas, C. and Rubio, F.R. Robustness improvement of a nonlinear H∞ controller for robot manipulators via saturation functions, J of Robotic Systems, 2005, 22, (8), pp 421-437.CrossRefGoogle Scholar
12. Castillo, P., Dzul, A. and Lozano, R. Real-time stabilization and tracking of a four-rotor mini rotorcraft, IEEE Transactions on Control Systems Technology, 2004, 12, (4), pp 510-516.CrossRefGoogle Scholar
13. Altug, E., Ostrowski, J.P. and Mahony, R. Control of a quadrotor helicopter using visual feedback, Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington, DC, USA, 2002, 1, pp 72-77.CrossRefGoogle Scholar
14. Altug, E., Ostrowski, J.P. and Taylor, C.J. Quadrotor control using dual cameral visual feedback, Proceedings of the 2003 IEEE International Conference on Robotics and Automation, Taipei, Taiwan, 2003, 3, pp 4294–4299.Google Scholar
15. Tayebi, A. and Mcgilvray, S. Attitude stabilization of a four-rotor aerial robot, Proceedings of the 2004 IEEE Conference on Decision and Control, Nassau, Bahamas, 2004, 2, pp 1216–1221.CrossRefGoogle Scholar
16. Bouabdallah, S. and Siegwart, R. Backstepping and sliding-mode techniques applied to an indoor micro quadrotor, Proceedings of the 2005 IEEE Conference on Robotics & Automation, Barcelona, Spain, 2005.Google Scholar
17. Bouabdallah, S., Murrieri, P. and Siegwart, R. Design and control of an indoor micro quadrotor, Proceedings of the 2004 IEEE Conference on Robotics & Automation, New Orleans, LA, USA, 2004.CrossRefGoogle Scholar
18. Beji, L., Abichou, A. and Zemalache, K.M. Smooth control of an X4 bidirectional rotors flying robot, 5th International Workshop on Robot Motion and Control, Dymaczewo, Poland, 2005.CrossRefGoogle Scholar
19. Shafiqul, I., Xiaoping, P.L. and Abdulmotaleb, E.S. Adaptive sliding mode control of unmanned four rotor flying vehicle, Int J of Robotics and Automation, 2015, 30, (2), pp 140-148.Google Scholar
20. Romero, H., Benosman, R. and Lozano, R. Stabilization and location of a four rotor helicopter applying vision, Proceedings of the 2006 American Control Conference, Minneapolis, NN, USA, 2006.CrossRefGoogle Scholar
21. Castillo, P., Lozano, R. and Dzul, A.E. Modeling and control of mini-flying machines, Advances in Industrial Control series, Springer Verlag, London, UK.Google Scholar
22. Castillo, P., Lozano, R. and Dzul, A.E. Stabilization of a mini-rotorcraft having four rotors, Proceedings of the 2004 IEEE Conference on Intelligent Robots and Systems, Sendai, Japan, 2004.Google Scholar
23. Castillo, P., Dzul, A.E. and Lozano, R. Real-time stabilization and tracking of a four rotor mini- rotorcraft, IEEE Transactions on Control Systems Technology, July 2004, 12, (4), pp 510-516.CrossRefGoogle Scholar
24. Zadeh, L.A. Soft computing and fuzzy logic, IEEE Software, 1994, 11, (6), pp 48-56.CrossRefGoogle Scholar
25. Reznik, L. Fuzzy Controllers, 1997, Newnes, Victoria University of Technology, Melbourne, Australia.Google Scholar
26. Passino, K.M. and Yurkovich, S. Fuzzy Control, 1998, Addison Wesley Longman, California, Menlo Park, US.Google Scholar
27. Mamdani, E.H. and Assilian, S. An experiment in linguistic synthesis with a fuzzy logic controller, Int J of Man-Machine Studies, 1975, 7, (1), pp 1-13.CrossRefGoogle Scholar
28. Precup, R.E. and Hellendoom, H. A survey on industrial applications of fuzzy control, Computers in Industry, 2011, 62, (3), pp 213-226.CrossRefGoogle Scholar
29. Manceur, M., Essounbouli, N. and Hamzaoui, A. Second order sliding fuzzy interval type-2 control for uncertain system with real application, IEEE Transactions on Fuzzy Systems, 2012, 20, (2), pp 262-275.CrossRefGoogle Scholar
30. Hussain, A., Essounbouli, N., Hamzaoui, A., Nollet, F. and Zaytoon, J. Type-2 fuzzy sliding mode control without reaching phase for nonlinear system, Engineering Applications of Artificial Intelligence, 2011, 24, (1), pp 23-38.Google Scholar
31. Cheng, S. and Li, C.W. Fuzzy PDFF-IIR controller for PMSM drive systems, Control Engineering Practice, 2011, 9, (8), pp 828-835.CrossRefGoogle Scholar
32. Mendes, J., Araujo, R., Sousa, P., Apostolo, F. and Alves, L. An architecture for adaptive fuzzy control in industrial environments, Computers in Industry, 2011, 62, (3), pp 364-373.CrossRefGoogle Scholar
33. ROSS, T.J. Fuzzy Logic with Engineering Applications, 3rd ed., 2010, John Wiley & Sons Ltd., the Atrium, Southern Gate, Chichester, West Sussex, UK.CrossRefGoogle Scholar
34. Mamdani, E.H. Applications of fuzzy algorithms for control of a simple dynamic plant, Proceedings of the IEE, 1974, 121, (12), pp 1585-1588.Google Scholar
35. Harkouss, Y., Accouch, O. and Issa, H. Design and implementation of fuzzy control for batch-type asphalt plant, Int. J. Internet Manufacturing and Services, Inderscience, 2013, 3, (2), pp 148-164.Google Scholar
36. Raza, S.A. and Gueaieb, W. Intelligent flight control of an autonomous quadrotor, Motion Control, Casolo, Federico (Ed.), 2010, InTech, published: under CC BY-NC-SA 3.0 License.Google Scholar
37. Santos, M., Lopez, V. and Morata, F. Intelligent fuzzy controller of a quadrotor, International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2010, pp 141–146, Hangzhou, China.CrossRefGoogle Scholar
38. Miller, D.S. Open Loop System Identification of a Micro Quadrotor Helicopter from Closed Loop Data, M.S. dissertation, 2011, University of Maryland, College Park, Maryland, US.Google Scholar
39. Dvorak, J. Micro Quadrotor-Design, Modeling, Identification and Control, M.S. Thesis, 2011, Czech Technical University, Prague, Czech Republic.Google Scholar
40. Bresciani, T. Modelling, Identification and Control of a Quadrotor Helicopter, M.S. Thesis, 2008, Lund University, Lund, Sweden.Google Scholar
41. Bouabdallah, S. Design and Control of Quadrotors with Application to Autonomous Wing, PhD Thesis, 2006, EPFL, Lausanne, Switzerland.Google Scholar
42. Pounds, P., Gresham, J., Corke, P., Roberts, J. and Mahony, R. Towards dynamically-favourable quad-rotor aerial robots, Proceedings Of Australasian Conference on Robotics and Automation, 2004, Canberra, Australia.Google Scholar
43. Hoffmann, G.M., Rajnarayan, D.G., Waslander, S.L., Dostal, D., Jang, J.S. and Tomlin, C.J. The Stanford testbed of autonomous rotorcraft for multi-agent control (STARMAC), The 23rd Digital Avionics Systems Conference, 2004, 2, 12.E.4- 121-10.Google Scholar
44. Seddon, J. Basic Helicopter Aerodynamics, 1990, BSP, London, UK.Google Scholar
45. Leishman, J.G. Principles of Helicopter Aerodynamics, 2nd ed, 2006, Cambridge University Press, London, UK.Google Scholar
46. Shamaa, D.A. Modeling and Identification of a Quadrotor, M.S. Thesis, 2015, Lebanese University, Faculty of Engineering, Lebanon.Google Scholar
47. Saied, M., Shamaa, D.A., Shraim, H., Francis, C., Lussier, B. and Fantoni, I. Model identification and validation for translational movements of an octorotor UAV, IEEE Workshop on Research, Education and Development of Unmanned Aerial Systems, November 2015, Cancun, Mexico, pp 102–108.CrossRefGoogle Scholar
48. Fang, Z., Zhi, Z., Jun, L. and Jian, W. Feedback linearization and continuous sliding mode control for a quadrotor UAV, Proceedings of the 27th Chinese Control Conference, July 2008, Kunming, Yunnan, China, pp 349–353.Google Scholar
49. Krayem, K. A Comparative Study for some Linear and Non-linear Controllers State of Art and Application on a Quadrotor Helicopter, M.S. Thesis, 2012, Lebanese University, Faculty of Engineering, Lebanon.Google Scholar
50. Kanellakopoulos, I. and Krein, P. Integral-action nonlinear control of induction motors, Proceedings of the 12th IFAC World Congress, 1993, Sydney, Australia.CrossRefGoogle Scholar
51. Tan, Y., Chang, J., He, J. and Tan, H. Advanced nonlinear control strategy for motion control systems, Proceedings of the IEEE Power Electronics and Motion Control Conference (PIEMC’00), 2000, Beijing, China.Google Scholar
52. Awada, A. A Comparative Study for the Application of Several Controllers on the Quadrotor based on a Frequency Analysis, M.S. Thesis, 2016, Lebanese University, Faculty of Engineering, Lebanon.Google Scholar