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Application of Robust Discontinuous Control Algorithm for a 5-DOF Industrial Robotic Manipulator in real-time

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Abstract

Robotic manipulators are nonlinear systems that are extensively used in industrial applications to perform many complex and specialized tasks which requires high precision and accurate trajectory tracking. This paper proposes the real-time implementation of a Robust Discontinuous Controller Algorithm to achieve trajectory tracking for a 5 degrees of freedom (DOF) robotic manipulator in a fast and accurate form with low chattering on the joint motors even under uncertainty and disturbance conditions. The trajectory design is developed by a fifth-order polynomial which ensures that robotic manipulator reaches the final desired position in a smooth way and enables to specify the endpoint positions, speeds and accelerations for each joint. A Lyapunov analysis is performed to guarantee system stability with the proposed controller algorithm. To verify the effectiveness of the proposed controller algorithm some simulations in Simulink\({}^{{\circledR }}\) environment are presented in comparison with a PD controller which is widely used for control of industrial robotic manipulators. Real time experimental results in a robotic manipulator CRS Catalyst-5 by Thermo Electron ®; are presented to support the simulation results and prove the effectiveness of the proposed controller.

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References

  1. Craig, J.J.: Introduction to Robotics: Mechanics and Control, 3/e. Pearson Education India, Chennai (2009)

    Google Scholar 

  2. Jazar, R.N.: Theory of Applied Robotics: Kinematics, Dynamics, and Control. Springer Science & Business Media, Berlin (2010)

    Book  Google Scholar 

  3. Kelly, R., Santibáñez, V: Control de movimiento de robots manipuladores. Automática y Robótica. Pearson Educación, Madrid (2003)

    Google Scholar 

  4. Arimoto, S., Miyazaki, F.: Stability and robustness of PID feedback control for robot manipulators of sensory capability. In: Brady, M., Paul, R.P. (eds.) Robotics research: First international symposium, pp 783–789. Cambridge: MIT Press. (1984)

  5. Sciavicco, L., Siciliano, B.: Modelling and control of robot manipulators. Springer Science & Business Media, Berlin (2012)

    MATH  Google Scholar 

  6. Chiacchio, P., Pierrot, F., Sciavicco, L., Siciliano, B.: Robust design of independent joint controllers with experimentation on a high-speed parallel robot. IEEE Trans. Ind. Electron. 40(4), 393–403 (1993)

    Article  Google Scholar 

  7. Craig, J.J., Hsu, P., Sastry, S.S.: Adaptive control of mechanical manipulators. Int. J. Rob. Res. 6(2), 16–28 (1987)

    Article  Google Scholar 

  8. Yang, Z.-J., Fukushima, Y., Qin, P.: Decentralized adaptive robust control of robot manipulators using disturbance observers. IEEE Trans. Control Syst. Technol. 20(5), 1357–1365 (2011)

    Article  Google Scholar 

  9. Wu, Y., Sun, N., Chen, H., Fang, Y.: Adaptive output feedback control for 5-dof varying-cable-length tower cranes with cargo mass estimation. IEEE Trans. Industr. Inform. (2020)

  10. Poignet, P., Gautier, M.: Nonlinear model predictive control of a robot manipulator. In: 6th International workshop on advanced motion control. Proceedings (Cat. No. 00TH8494), pp 401–406. IEEE (2000)

  11. Chang, W., Li, Y., Tong, S.: Adaptive fuzzy backstepping tracking control for flexible robotic manipulator. IEEE/CAA Journal of Automatica Sinica (2018)

  12. Chaudhary, H., Panwar, V., Prasad, R., Sukavanam, N.: Adaptive neuro fuzzy based hybrid force/position control for an industrial robot manipulator. J. Intell. Manuf. 27(6), 1299–1308 (2016)

    Article  Google Scholar 

  13. Yang, T., Sun, N., Chen, H., Fang, Y.: Neural network-based adaptive antiswing control of an underactuated ship-mounted crane with roll motions and input dead zones. IEEE Trans. Neural. Netw. Learn. Syst. 31(3), 901–914 (2019)

    Article  MathSciNet  Google Scholar 

  14. Slotine, J.-J., Sastry, S.S.: Tracking control of non-linear systems using sliding surfaces, with application to robot manipulators. Int. J. Control 38(2), 465–492 (1983)

    Article  Google Scholar 

  15. Slotine, J.-J.E.: Sliding controller design for non-linear systems. Int. J. Control 40(2), 421–434 (1984)

    Article  MathSciNet  Google Scholar 

  16. Zeinali, M., Notash, L.: Adaptive sliding mode control with uncertainty estimator for robot manipulators. Mech. Mach. Theory 45(1), 80–90 (2010)

    Article  MathSciNet  Google Scholar 

  17. Zhu, M., Li, Y.: Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators. Int. J. Robust Nonlinear Control: IFAC-Affiliated J. 20 (4), 472–488 (2010)

    Article  MathSciNet  Google Scholar 

  18. Yi, S., Zhai, J.: Adaptive second-order fast nonsingular terminal sliding mode control for robotic manipulators. ISA Trans. 90, 41–51 (2019)

    Article  Google Scholar 

  19. Ouyang, P.R., Acob, J., Pano, V.: Pd with sliding mode control for trajectory tracking of robotic system. Robot. Comput. Integr. Manuf. 30(2), 189–200 (2014)

    Article  Google Scholar 

  20. Amer, A.F., Sallam, E.A., Elawady, W.M.: Adaptive fuzzy sliding mode control using supervisory fuzzy control for 3 dof planar robot manipulators. Appl. Soft Comput. 11(8), 4943–4953 (2011)

    Article  Google Scholar 

  21. Zhihong, M., Paplinski, A.P., Wu, H.R.: A robust mimo terminal sliding mode control scheme for rigid robotic manipulators. IEEE Trans. Automat. Contr. 39 (12), 2464–2469 (1994)

    Article  MathSciNet  Google Scholar 

  22. Utkin, V., Guldner, J., Shi, J.: Sliding Mode Control in Electro-Mechanical Systems. CRC Press, Cleveland (2017)

    Book  Google Scholar 

  23. Edwards, C., Spurgeon, S.: Sliding Mode control: Theory and Aapplications. CRC Press, Cleveland (1998)

    Book  Google Scholar 

  24. Mondal, S., Mahanta, C.: Adaptive second order terminal sliding mode controller for robotic manipulators. J. Franklin Inst. 351(4), 2356–2377 (2014)

    Article  MathSciNet  Google Scholar 

  25. Hušek, P: Adaptive sliding mode control with moving sliding surface. Appl. Soft Comput. 42, 178–183 (2016)

    Article  Google Scholar 

  26. Levant, A.: Principles of 2-sliding mode design. Automatica 43(4), 576–586 (2007)

    Article  MathSciNet  Google Scholar 

  27. Jeong, C.-S., Kim, J.-S., Han, S.-I.: Tracking error constrained super-twisting sliding mode control for robotic systems. Int. J. Control. Autom. Syst. 16(2), 804–814 (2018)

    Article  Google Scholar 

  28. Mobayen, S., Tchier, F., Ragoub, L.: Design of an adaptive tracker for n-link rigid robotic manipulators based on super-twisting global nonlinear sliding mode control. Int. J. Syst. Sci. 48(9), 1990–2002 (2017)

    Article  MathSciNet  Google Scholar 

  29. Cruz, G.L., Alazki, H., Hernández, R G: Super twisting control for thermo’s catalyst-5 robotic arm. IFAC-PapersOnLine 51(13), 303–308 (2018)

    Article  Google Scholar 

  30. Chalanga, A., Kamal, S., Fridman, L.M., Bandyopadhyay, B., Moreno, J.A.: Implementation of super-twisting control: Super-twisting and higher order sliding-mode observer-based approaches. IEEE Trans. Ind. Electron. 63(6), 3677–3685 (2016)

    Article  Google Scholar 

  31. Tutsoy, O., Calikusu, I., Colak, S., Vahid, O., Barkana, D.E., Gongor, F.: Developing linear and nonlinear models of abb irb120 industrial robot with maplesim multibody modelling software. Eurasia Proc. Sci. Technol. Eng. Math 1, 273–285 (2017)

    Google Scholar 

  32. Shtessel, Y., Edwards, C., Fridman, L., Levant, A.: Sliding Mode Control and Observation, vol. 10. Springer, Berlin (2014)

    Book  Google Scholar 

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This research received no specific grant from any funding agency.

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Authors and Affiliations

  1. Faculty of Engineering, Universidad Autonoma del Carmen, Campeche, Mexico

    Giovanni Lopez Cruz, Hussain Alazki & José Luis Rullán-Lara

  2. Faculty of Electrical Engineering, Universidad Michoacana de San Nicolas de Hidalgo, Morelia, Mexico

    David Cortes-Vega

Authors
  1. Giovanni Lopez Cruz
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  2. Hussain Alazki
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  3. David Cortes-Vega
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  4. José Luis Rullán-Lara
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Correspondence to Hussain Alazki.

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Cruz, G.L., Alazki, H., Cortes-Vega, D. et al. Application of Robust Discontinuous Control Algorithm for a 5-DOF Industrial Robotic Manipulator in real-time. J Intell Robot Syst 101, 75 (2021). https://doi.org/10.1007/s10846-020-01282-1

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  • DOI: https://doi.org/10.1007/s10846-020-01282-1

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