Research PaperNo Access

Robust Control of Golf Swing Robot Using Backstepping Based on Fuzzy Sliding-Mode and Super-Twisting Backstepping Sliding-Mode Algorithms

Souhila Benmansour

https://orcid.org/0000-0001-9598-5604

AVCIS Laboratory, University of Sciences and Technology of Oran Mohamed-Boudiaf Oran, Algeria

E-mail Address: souhila_benmansour@yahoo.fr

Corresponding author.

Search for more papers by this author

Fethi Demim

Laboratory of Guidance and Navigation, Ecole Militaire Polytechnique, Bordj El Bahri, Algiers, Algeria

E-mail Address: demifethi@gmail.com

Search for more papers by this author

, and

Ali Zakaria Messaoui

Laboratory of Complex Systems Control and Simulators, Ecole Militaire Polytechnique, Bordj El Bahri, Algiers, Algeria

E-mail Address: alizakariamessaoui@gmail.com

Search for more papers by this author

https://doi.org/10.1142/S2301385025500268Cited by:1 (Source: Crossref)

Abstract

This paper focuses on trajectory tracking, robustness and stabilization of a golf swing robot which has been recently developed to simulate the ultra-high-speed swing motions of a golfer. The proposed control strategies are based on the Lyapunov stability theory and include Backstepping and Sliding-Mode Control based techniques. To attenuate the chattering phenomena caused by a discontinuous switching function and improve the dynamic response of the manipulator, a fuzzy system is used in this research; a Backstepping Sliding-Mode Controller (BSMC), a Backstepping Fuzzy Sliding-Mode Controller (BFSMC) and a Super-twisting Backstepping Sliding-Mode Controller (STBSMC) are used to evaluate the proposed hybrid controller’s BFSMC performance. The Lyapunov stability theory is used to guarantee the stability of the proposed closed-loop robot technique. Numerical simulations show the effectiveness of the proposed strategy based on the fuzzy logic mechanism under different disturbances and uncertainties.

This paper was recommended for publication in its revised form by editorial board member, Ying Tan.

Keywords:

References

1. A. Ming and M. Kajitani, Human dynamic skill in high speed actions and its realization by robot, J. Robot. Mechatron. 12 (2000) 318–334. Google Scholar
2. A. Ming, T. Mita, S. Dhlamini and M. Kajitani, Motion control skill in human hyper dynamic manipulation an investigation on the golf swing by simulation, in Proc. 2001 IEEE Int. Symp. Computational Intelligence in Robotics and Automation (IEEE, 2001), pp. 47–52. Google Scholar
3. C. Xu, A. Ming, T. Maruyama and M. Shimojo, Motion generation for hyper dynamic manipulation, Mechatronics 17 (2007) 405–416. Google Scholar
4. M. Aicardi, A triple pendulum robotic model and a set of simple parametric functions for the analysis of the golf swing, Int. J. Sports Sci. Eng. 1 (2007) 75–86. Google Scholar
5. Y. Hoshino, Y. Kobayashi and G. Yamada, Vibration control using a state observer that considers disturbances of a golf swing robot, JSME Int. J. Ser. C, Mech. Syst. Mach. Elem. Manuf. 48 (2005) 60–69. Google Scholar
6. Z. W. Li, I. Yoshio, K. Shunta and S. Kyoko, The effect of swing pattern on the release point and the club head speed, in Proc. 3th Int. Conf. Multibody System Dynamics (South Korea, 2014). Google Scholar
7. S. J. MacKenzie, Club position relative to the golfer’s swing plane meaningfully affects swing dynamics, Sports Biomech. 11 (2012) 149–164. Google Scholar
8. S. Coleman and D. Anderson, An examination of the planar nature of golf club motion in the swings of experienced players, J. Sports Sci. 7 (2007) 739–748. Google Scholar
9. A. Ming and C. Xu, Human-inspired hyper dynamic manipulation, in Biologically Inspired Robotics (CRC Press, Boca Raton, 2012), pp. 55–84. Google Scholar
10. S. Benmansour, A. Omari and K. Z. Meguenni, Optimizing motion planning for hyper dynamic manipulator, J. Electr. Eng. 1 (2012) 21–27. Google Scholar
11. S. Benmansour, A. Omari and K. Z. Meguenni, Motion planning and control of hyper dynamic robot arm, Int. Rev. Autom. Control 7 (2014) 82–89. Google Scholar
12. A. Omari and S. Benmansour, Comparative study on optimal motion planning based genetic algorithm for hyper dynamic robot arm, Mediterr. J. Meas. Control 8(3) (2012) 456–466. Google Scholar
13. C. Xu, A. Ming and M. Shimojo, Motion planning for a golf swing robot based on reverse time symmetry and PGCTC control, in Proc. 2009 IEEE Int. Conf. Robotics and Automation (2009), pp. 69–74. Google Scholar
14. C. Xu, Z. Z. Yang, A. G. Ming and M. Shimojo, Motion planning of golf swing robot, Mechatronics 22 (2012) 13–23. Google Scholar
15. S. Benmansour, Generation de mouvement optimal et commande d’un bras manipulateur hyper dynamique, Ph.D. thesis, Department of Automation, University of Sciences and Technology Mohamed Boudiaf, Algeria (2016). Google Scholar
16. S. Benmansour, A. Omari and K. Z. Meguenni, H $_{\infty}$ observer based computed torque for hyper dynamic manipulator, in Proc. Int. Conf. Automation and Mechatronics (Oran, Algeria, 2011). Google Scholar
17. S. Benmansour, F. Demim and A. Omari, Design of a sliding mode observer based on computed torque control for hyper dynamic manipulation, J. Eur. Syst. Autom. 52 (2019) 449–456. Google Scholar
18. S. Benmansour, F. Demim and A. Z. Messaoui, Fuzzy integral sliding mode control of a hyperdynamic golf swing robot, in Proc. 5th Conf. Electrical Engineering and Control Applications (2022). Google Scholar
19. M. Krstic and A. Smyshlyaev, Boundary Control of PDEs: A Course on Backstepping Designs (Society for Industrial and Applied Mathematics, Phildelphia, 2008). Google Scholar
20. Y. Yu, Z. Li, Z. Yang and Z. Ding, Distributed back-stepping consensus protocol for attitude synchronization and tracking on undirected graphs, Unmanned Syst. 7(1) (2019) 25–32. Link, Google Scholar
21. Y. Peng, L. Guo and Q. Meng, Backstepping control strategy of an autonomous underwater vehicle based on probability gain, Mathematics 10 (2022) 3958. Google Scholar
22. H. Hu, Y. Song, P. Fan, C. Diao and N. Cai, A backstepping controller with the RBF neural network for folding-boom aerial work platform, Complexity 2022 (2022) 4289111. Google Scholar
23. K. Noussi, A. Aouloifa, H. Katir, I. Lachkar, C. Aouadi, M. Aourir and F. El Otmani, Integral backstepping control based on high gain observer for DFIG based wind energy conversion system, IFAC-PapersOnLine 55(12) (2022) 653–658. Google Scholar
24. S. Li, X. Yu, L. Fridman, Z. Man and X. Wang, Advances in Variable Structure Systems and Sliding Mode Control: Theory and Applications, Studies in Systems, Decision and Control (Springer International Publishing, Cham, 2017). Google Scholar
25. F. Zhang, J. Maddy, G. Premier and A. Guwy, Novel current sensing photovoltaic maximum power point tracking based on sliding mode control strategy, Sol. Energy 118 (2015) 80–86. Google Scholar
26. V. Utkin, J. Guldner and J. X. Shi (eds.), Sliding Mode Control in Electro-Mechanical Systems, 2nd edn. (CRC Press, Boca Raton, 2009). Crossref, Google Scholar
27. Y. Xie, X. Zhang, L. Jiang, J. Meng, G. Li and S. Wang, Sliding-mode disturbance observer-based control for fractional-order system with unknown disturbances, Unmanned Syst. 8(3) (2020) 193–202. Link, Google Scholar
28. B. Wang and Y. Zhang, Adaptive sliding mode fault-tolerant control for an unmanned aerial vehicle, Unmanned Syst. 5(4) (2017) 209–221. Link, Google Scholar
29. Y. Shtessel, C. Edwards, L. Fridman and A. Levant, Sliding Mode Control and Observation (Springer Science+Business Media, New York, 2014). Crossref, Google Scholar
30. I. Castillo, L. Fridman and J. A. Moreno, Super-twisting algorithm in presence of time and state dependent perturbations, Int. J. Control 91 (2018) 2535–2548. Google Scholar
31. F. Mohd Zaihidee, S. Mekhilef and M. Mubin, Robust speed control of PMSM using sliding mode control (SMC): A review, Energies 12 (2019) 1669. Google Scholar
32. C. Mohan (ed.), An Introduction to Fuzzy Set Theory and Fuzzy Logic, 2nd edn. (Viva Books, 2017). Google Scholar
33. B. Jiang, H. R. Karimi, Y. Kao and C. Gao, Takagi-Sugeno model based event-triggered fuzzy sliding-mode control of networked control systems with semi-Markovian switchings, IEEE Trans. Fuzzy Syst. 28(4) (2020) 673–683. Google Scholar
34. F. Demim, A. Nemra, K. Louadj and M. Hamerlain, Simultaneous localization, mapping, and path planning for unmanned vehicle using optimal control, Adv. Mech. Eng. 10 (2018) 1687814017736653. Google Scholar
35. A. Kchaou, A. Naamane, Y. Koubaa and N. M’sirdi, Second order sliding mode-based MPPT control for photovoltaic applications, Sol. Energy 155 (2017) 758–769. Google Scholar
36. A. Chalanga, S. Kamal, L. M. Fridman, B. Bandyopadhyay and J. A. Moreno, Implementation of super-twisting control: Super-twisting and higher order sliding-mode observer-based approaches, IEEE Trans. Ind. Electron. 63 (2016) 3677–3685. Google Scholar
37. C. Xu, A. Ming, K. Mak and M. Shimojo, Design for high dynamic performance robot based on dynamically coupled driving and joint stop, Int. J. Robot. Autom. 22 (2007) 281–293. Google Scholar
38. H. Bouadi, M. Bouchoucha and M. Tadjine, Sliding mode control based on backstepping approach for an UAV type-quadrotor, World Acad. Sci. Eng. Technology, Int. J. Mech. Mechatron. Eng. 1(2) (2007) 39–44. Google Scholar
39. S. Vaidyanathan and C. H. Lien (eds.), Applications of Sliding Mode Control in Science and Engineering, Studies in Computational Intelligence, Vol. 709 (Springer International Publishing, 2017). Google Scholar
40. L. Derafa, A. Benallegue and L. Fridman, Super twisting control algorithm for the attitude tracking of a four rotors UAV, J. Frankl. Inst. 349(2) (2012) 685–699. Crossref, Google Scholar
41. J. A. Moreno and M. Osorio, Strict Lyapunov functions for the supertwisting algorithm, IEEE Trans. Autom. Control 57 (2012) 1035–1040. Google Scholar