Advertisement

Flexible-Link Manipulators: Dynamic Analysis and Advanced Control Strategies

  • R. BoucettaEmail author
  • S. Hamdi
  • S. Bel Hadj Ali
Chapter
  • 3 Downloads
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 270)

Abstract

This chapter contains advanced studies in dynamic modelling and nonlinear control strategies applied to flexible-link robotic manipulators increasingly in demand in many fields such as industrial domain, medical intervention, and space exploitation. Taking into consideration the flexibility effect, Hamilton’s principle and Euler–Lagrange equations are associated to determine a highly nonlinear and coupled dynamic model. Therefore, the main control goals are to reach a perfect trajectory tracking without vibration impact. That is why, PD, Fuzzy, and gain scheduling Fuzzy PD controllers are applied to a rigid-flexible two links manipulator and then compared in terms of robustness and vibration minimization. A stability study is accomplished using the candidate function of Lyapunov. To improve performances, a robust Fractional Order Fuzzy PD (FOFPD) controller is developed by using non-integer order differentiator operators in the fuzzy PD controller. The gains of the FOFPD are normalized with the Particle Swarm Optimization (PSO) algorithm. The small gain theorem is used to establish the sufficient condition for bounded input-bounded output (BIBO) stability in closed-loop. Simulation results are introduced for each case of control to discuss reached performances.

Keywords

Rigid-flexible manipulator Dynamic model PD control Fuzzy control Fractional order fuzzy control Particle Swarm Optimization 

Notes

Acknowledgements

This work was supported by the Ministry of the Higher Education and Scientific Research in Tunisia.

References

  1. 1.
    Abe, A.: Trajectory planning for residual vibration suppression of a two-link rigid-flexible manipulator considering large deformation. Elsevier Mech. Mach. Theorye 44(9), 1627–1639 (2009)CrossRefGoogle Scholar
  2. 2.
    Alavandar, S., Jain, T., Nigam, M.J.: Bacterial foraging optimized hybrid fuzzy precompensated pd control of two link rigid-flexible manipulator. Int. J. Comput. Intell. Syst. 2(1), 51–59 (2009)Google Scholar
  3. 3.
    Baroudi, M., Saad, M., Ghie, W.: State-feedback and linear quadratic regulator applied to a single-link flexible manipulators. IEEE International Conference on Robotics and Biomimetics. IEEE Press, Guilin (2009)Google Scholar
  4. 4.
    Bayo, E.: A finite-element approach to control the end-point motion of a single-link flexible robot. J. Robot. Syst. 4(1), 63–75 (1987)CrossRefGoogle Scholar
  5. 5.
    Boucetta, R., Belhadjali, S., Abdelkrim, M.N.: Global hybrid fuzzy controller for a flexible single-link manipulator. J. Eng. Appl. Sci. 6(1), 1–5 (2011)Google Scholar
  6. 6.
    Cao, F., Liu, J.: Boundary control for a constrained two-link rigid-flexible manipulator with prescribed performance. Int. J. Control 90(5), 1–13 (2017)MathSciNetGoogle Scholar
  7. 7.
    Chanwikrai, S., Cole, M.O.: Modeling of a rigid-flexible manipulator using hamilton’s principle. Engng. J. CMU 17(3), 19–27 (2008)Google Scholar
  8. 8.
    Chen, G., Pham, T.T.: Introduction to fuzzy systems. CRC Press, Boca Raton (2005)CrossRefGoogle Scholar
  9. 9.
    Cost, A., Jos, S.D.A.: An introduction to fractional control. Institution of Engineering and Technology, London (2013)Google Scholar
  10. 10.
    Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: IEEE Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Nagoya (1995)Google Scholar
  11. 11.
    Fenili, A.: The rigid-flexible robotic manipulator: nonlinear control and state estimation considering a different mathematical model for estimation. Hindawi Publ. Corp. Shock. Vib. 20(6), 1049–1063 (2013)Google Scholar
  12. 12.
    Fenili, A., Balthazar, J.: The rigid-flexible nonlinear robotic manipulator: modeling and control. Commun. Nonlinear Sci. Numer. Simul. 16(5), 2332–2341 (2011)CrossRefGoogle Scholar
  13. 13.
    Gao, H., He, W.: Fuzzy control of a single-link flexible robotic manipulator using assumed mode method. In: IEEE Youth Academic Annual Conference of Chinese Association of Automation (YAC), Wuhan (2016)Google Scholar
  14. 14.
    Gao, Y., Er, M.J., Leithead, W.E., Leith, D.J. Online adaptive control of robot manipulators using dynamic fuzzy neural networks. In: IEEE Proceedings American Control Conference (2001)Google Scholar
  15. 15.
    Hamdi, S., Boucetta, R., Belhadjali, S.: Dynamic modeling of a rigid-flexible manipulator using Hamilton’s principle. In: IEEE International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA) (2015)Google Scholar
  16. 16.
    He, W., David, A.O., Yin, Z., Sun, C.: Neural network control of a robotic manipulator with input deadzone and output constraint. IEEE Trans. Syst. Man Cybern. Syst. 46(6), 759–770 (2016)Google Scholar
  17. 17.
    Hong, J., He, W., Le, Z., Zhang, S.: Vibration control and angular tracking of a flexible link via neural networks. In: IEEE Control and Decision Conference, Chinese (CCDC) (2015)Google Scholar
  18. 18.
    Irani, A., Talebi, H.: Tip tracking control of a rigid-flexible manipulator based on deflection estimation using neural networks: application to needle insertion. In: IEEE ISSNIP Biosignals and Biorobotics Conference (2011)Google Scholar
  19. 19.
    Kumar, V., Mittal, A.P.: Parallel fuzzy p\(+\) fuzzy i\(+\) fuzzy d controller: design and performance evaluation. Int. J. Autom. Comput. 7(4), 463–471 (2010)CrossRefGoogle Scholar
  20. 20.
    Lee, H.H., Liang, Y.: A coupled-sliding-surface approach for the robust trajectory control of a horizontal two-link rigid-flexible robot. Int. J. Control. 80(12), 1880–1892 (2007)Google Scholar
  21. 21.
    Lochan, K., Roy, B.K., Subudhi, B.: Smc controlled chaotic trajectory tracking of two-link flexible manipulator with pid sliding surface. IFAC-PapersOnLine 49(1), 219–224 (2016)CrossRefGoogle Scholar
  22. 22.
    Monje, C.A., Chen, Y., Vinagre, B.M., Xue, D., Feliu-Batlle, V.: Fractional-Order Systems and Controls: Fundamentals and Applications. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  23. 23.
    Qiu, Z., Zhao, Z.: Pneumatic drive active vibration control for flexible manipulator using an adaptive interactive PD controller. In: Communications in Nonlinear Science and Numerical Simulation (2011)Google Scholar
  24. 24.
    Sabatier, J., Lanusse, P., Melchior, P., Oustaloup, A.: Fractional Order Differentiation and Robust Control Design: CRONE, H-infinity and Motion Control. Springer, Berlin (2015)CrossRefGoogle Scholar
  25. 25.
    Spong, M., Hutchinson, S., Vidyasagar, M.: Robot Modeling and Control. Wiley, New York (2006)Google Scholar
  26. 26.
    Sun, C., He, W., Hong, J.: Neural network control of a flexible robotic manipulator using the lumped spring-mass model. IEEE Trans. Syst. Man Cybern. 47, 1863–1874 (2016)CrossRefGoogle Scholar
  27. 27.
    Hussein, T.M., Nemah, M.N.: Control of a two-link rigid-flexible manipulator. In: IEEE International Conference on Robotics and Mechatronics (ICROM) (2015)Google Scholar
  28. 28.
    Tarvirdizadeh, B., Alipour, K.: Trajectory optimization of two-link rigid flexible manipulators in Dynamic Object Manipulation missions. In: IEEE International Conference on Robotics and Mechatronics (ICROM) (2015)Google Scholar
  29. 29.
    Tian, L., Collins, C.: A dynamic recurrent neural network-based controller for a rigid-flexible manipulator system. Mechatronics 14(5), 471–490 (2004)CrossRefGoogle Scholar
  30. 30.
    Tian, L., Mao, Z.: Fuzzy neuro controller for a two-link rigid-flexible manipulator system. In: Proceedings of the 9th Internatioal Conference on IEEE Neural Information Processing. ICONIP’02 (2002)Google Scholar
  31. 31.
    Tinkir, M., Önen, Ü., Kalyoncu, M.: Modelling of neurofuzzy control of a flexible link. SAGE Publ. Proc. Inst. Mech. Eng. 224(5), 529–543 (2010)Google Scholar
  32. 32.
    Xilun, D., Selig, J.M.: Lumped parameter dynamic modeling for the flexible manipulator. In: IEEE Intelligent Control and Automation, WCICA 2004. Fifth World Congress (2004)Google Scholar
  33. 33.
    Ying, H.: Fuzzy control and modeling: analytical foundations and applications. Wiley-IEEE Press, Hoboken (2000)CrossRefGoogle Scholar
  34. 34.
    Zhang, S., Zhang, Y., Zhang, X., Dong, G.: Fuzzy pid control of a two-link flexible manipulator. J. Vibroengineering 18(1), 250–266 (2016)MathSciNetGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Physics Department, Sciences Faculty of SfaxUniversity of SfaxSfaxTunisia
  2. 2.MACS Laboratory, National Engineering School of GabesUniversity of GabesGabesTunisia
  3. 3.Preparatory Institute of Tunis El ManarUniversity of Tunis El ManarTunisTunisia

Personalised recommendations