Journal of Mechanical Science and Technology

, Volume 32, Issue 2, pp 875–884 | Cite as

Finite-time sliding mode joint positioning error constraint control for robot manipulator in the presence of unknown deadzone

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Abstract

This paper proposes two tracking error constraint finite-time sliding mode control schemes for unknown manipulator parameters with deadzone input nonlinearity. A transformed filtered tracking error surface was first constructed as a separated form to guarantee the predefined tracking performance. Next, a simple transformed prescribed error surface was considered to obtain the same predefined tracking performance. Both proposed controls adopt Finite-time sliding mode control (FSMC) with a non-model-based manipulator feedforward method to achieve rapid error convergence and fast control design. Unlike conventional controls with deazone compensation, the proposed controls are robust to deadzone nonlinearity without adding extra compensators. The effectiveness of the proposed scheme was proven by simulation and experimental evaluations for an articulated manipulator system with unknown deadzone and friction.

Keywords

Robot manipulator Finite-time sliding mode control Tracking error constraint control Joint deadzone 

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References

  1. [1]
    S. Kalpakjian and S. R. Schmid, Manufacturing processes for engineering materials, Second Ed., Addison-Wesley Publishing Company, New York, USA (1992).Google Scholar
  2. [2]
    J. J. Craig, P. Hsu and S. S. Sastry, Adaptive control of mechanical manipulators, Inter. J. of Robotics Research, 6 (2) (1987) 16–28.CrossRefGoogle Scholar
  3. [3]
    J. J. E. Slotine and W. Li, On the adaptive control of robot manipulator, Inter. J. of Robotics Research, 6 (3) (1987) 49–59.CrossRefGoogle Scholar
  4. [4]
    J. J. E. Slotine and W. Li, Composite adaptive control of robot manipulator, Automatica, 25 (1989) 509–519.MathSciNetCrossRefMATHGoogle Scholar
  5. [5]
    R. Johansson, Adaptive control of robot manipulator motion, IEEE Trans. Robotics and Auto., 6 (4) (1990) 483–490.CrossRefGoogle Scholar
  6. [6]
    B. K. Yoo and W. C. Ham, Adaptive control of robot manipulator using fuzzy compensator, IEEE Trans. Fuzzy Sys., 8 (2) (2000) 186–199.CrossRefGoogle Scholar
  7. [7]
    E. Kim, Output feedback tracking control of robot manipulators with model uncertainty via adaptive fuzzy logic, IEEE Trans. Indust. Electr., 12 (3) (2004) 368–378.MathSciNetGoogle Scholar
  8. [8]
    F. Sun, Z. Sun and P. Y. Woo, Neural network-based adaptive controller design of robotic manipulators with an observer, IEEE Trans. Neural Net., 12 (1) (2001) 54–67.MathSciNetCrossRefGoogle Scholar
  9. [9]
    S. Lin and A. A. Golgenberg, Neural-network control of mobile manipulator, IEEE Trans. Neural Net., 12 (5) (2001) 1121–1133.CrossRefGoogle Scholar
  10. [10]
    J. J. E. Slotine and W. Li, Applied nonlinear control, Prentice Hall, New Jersey (1991).MATHGoogle Scholar
  11. [11]
    V. J. Ukin, J. Guldner and J. Shi, Sliding mode control in Electro-mechanical systems, 2nd Edition, CRC Press, New York (2009).CrossRefGoogle Scholar
  12. [12]
    A. Ebrahimi, Regulated model-based and non-model-based sliding mode control of a MEMS vibratory gyroscope, J. Mechanical Science and Tech., 28 (6) (2014) 2343–2349.MathSciNetCrossRefGoogle Scholar
  13. [13]
    J. Aslam, S. Y. Qin and M. A. Alvi, Fuzzy sliding mode control algorithm for a four-wheel skid steer vehicle, J. Mechanical Science and Tech., 28 (8) (2014) 3301–3310.CrossRefGoogle Scholar
  14. [14]
    J. H. Lee, Y. W. Yun, H. W. Hong and M. K. Park, Control of spool position of on/off solenoid operated hydraulic valve by sliding mode controller, J. Mechanical Science and Tech., 29 (12) (2015) 5395–5408.CrossRefGoogle Scholar
  15. [15]
    L. W. Lee and I. H. Li, Design and implementation of a robust FNN-based adaptive sliding mode controller for pneumatic actuator systems, J. Mechanical Science and Tech., 30 (1) (2016) 381–396.CrossRefGoogle Scholar
  16. [16]
    F. L. Lewis, W. K. Tim, L. Z. Wang and Z. X. Li, Deadzone compensation in motion control systems using adaptive fuzzy control, IEEE Trans. Control Sys. and Tech., 7 (6) (1999) 731–742.CrossRefGoogle Scholar
  17. [17]
    C. Hu, B. Yao and Q. Wang, Performance-oriented adaptive robust control of a class of nonlinear systems preceded by unknown dead zone with comparative experimental results, IEEE/ASME Trans. Mechatronics, 18 (1) (2013) 178–189.CrossRefGoogle Scholar
  18. [18]
    C. Hu, B. Yao and Q. Wang, Adaptive robust precision motion control of systems with unknown input dead-zones: A case study with comparative experiments, IEEE Trans. Industrial Elect., 58 (6) (2011) 2454–2464.CrossRefGoogle Scholar
  19. [19]
    Y. Feng, X. Yu and Z. Man, Non-singular terminal sliding mode control of rigid manipulator, Automatica, 38 (12) (2002) 2159–2167.MathSciNetCrossRefMATHGoogle Scholar
  20. [20]
    S. Yu, X. Yu, B. Shirinzadeh and Z. Man, Continuous finite-time control for robotic manipulators with terminal sliding mode, Automatica, 41 (11) (2005) 1957–1964.MathSciNetCrossRefMATHGoogle Scholar
  21. [21]
    D. Zhao, S. Li and Q. Zhu, Output feedback terminal sliding mode control for a class of second order nonlinear systems, Asian J. Control, 15 (1) (2013) 237–247.MathSciNetCrossRefMATHGoogle Scholar
  22. [22]
    C. P. Benchlioulis and G. A. Rovithakis, Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance, IEEE Trans. A. C., 53 (9) (2008) 2090–2099.MathSciNetCrossRefMATHGoogle Scholar
  23. [23]
    C. P. Benchlioulis and G. A. Rovithakis, Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems, Automatica, 45 (2009) 532–538.MathSciNetCrossRefMATHGoogle Scholar
  24. [24]
    W. Wang and C. Wen, Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance, Automatica, 46 (2010) 2082–2091.MathSciNetCrossRefMATHGoogle Scholar
  25. [25]
    J. Na, Q. Chen, X. Ren and Y. Guo, Adaptive prescribed performance motion control of servo mechanisms with friction compensation, IEEE Trans. Indust. Electr., 61 (1) (2014) 486–494.CrossRefGoogle Scholar
  26. [26]
    A. Theodorakopoulos and G. A. Rovithakis, Prescribed performance control of strict feedback systems with deadzone input nonlinearity, 52nd IEEE Confer. On Decision and Control (2013) 1774–1779.CrossRefGoogle Scholar
  27. [27]
    A. Theodorakopoulos and G. A. Rovithakis, Guaranteeing preselected tracking quality for uncertain strict-feedback with deadzone input nonlinearity and disturbance via lowcomplexity control, Automatica, 54 (2015) 135–145.MathSciNetCrossRefMATHGoogle Scholar
  28. [28]
    Z. P. Wang, S. S. Ge and T. H. Lee, Robust motion/force control of uncertain holonomic/nonholonomic mechanical systems, IEEE Trans. Mechatronics, 9 (1) (2004) 118–123.CrossRefGoogle Scholar
  29. [29]
    S. I. Han and J. Lee, Partial tracking error constrained fuzzy dynamic surface control for a strict feedback nonlinear dynamic system, IEEE Trans. Fuzzy Sys., 22 (5) (2014) 1049–1061.CrossRefGoogle Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringTongmyong UniversityBusanKorea
  2. 2.School of Mechanical of EngineeringPusan National UniversityBusanKorea

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