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Switching Motion Control of Aircraft Skin Inspection Robot Using Backstepping Scheme and Nussbaum Disturbance Observer

  • Congqing Wang
  • Junjun Jiang
  • Xuewei Wu
  • Linfeng Wu
Regular Papers Robot and Applications
  • 14 Downloads

Abstract

In this paper, a backstepping control using switching strategy is proposed for the motion control of the aircraft skin inspection robot with double frame in the presence of external disturbances. The inspection robot equipped with a CCD camera and an ultrasonic sensor can alternately adsorb and move on the aircraft surface. The influence of the external disturbances is obvious in the switching motion. The disturbances are efficiently estimated using a Nussbaum disturbance observer (NDO), and the disturbance observer errors are uniformly ultimately bounded. Then, the backstepping control method is used to design the motion controller. The stability of the closed-loop robot system is proved by Lyapunov analysis through the average dwell time method.The tracking errors and the disturbance observer errors are semi-globally uniformly bounded using the proposed control scheme with NDO,and NDO is compared with Super-twisting disturbance observer. Finally, simulation results illustrate that the proposed control scheme with NDO can achieve satisfactory tracking performance under the external disturbance.

Keywords

Aircraft skin inspection robot backstepping control disturbance observer motion control 

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References

  1. [1]
    M. W. Siegel, W. M. Kaufman, and C. J. Alberts, “Mobile robots for difficult measurements in difficult environments: Application to aging aircraft inspection,” Robotics & Autonomous Systems, vol. 11, no. 3–4, pp. 187–194, December 1993.Google Scholar
  2. [2]
    M. W. Siegel, P. Gunatilake, and G. Podnar, “Robotic assistants for aircraft inspectors,” IEEE Instrumentation & Measurement Magazine, vol. 1, no. 1, pp. 16–30, March 1998.Google Scholar
  3. [3]
    T. S. White, R. Alexander, G. Callow, A. Cooke, S. Harris, and J. Sargent, “A Mobile climbing robot for high precision manufacture and inspection of aerostructures,” International Journal of Robotics Research, vol. 24, no. 7, pp. 589–598, July 2005.Google Scholar
  4. [4]
    J. Shang, T. Sattar, S. Chen, and B. Bridge, “Design of a climbing robot for inspecting aircraft wings and fuselage,” Industrial Robot, vol. 34, no. 34, pp. 495–502, October 2007.Google Scholar
  5. [5]
    H. Moradi and V. J. Majd, “Dissipativity-based stable controller redesign for nonlinear MIMO switched systems in the presence of perturbations,” Nonlinear Dynamics, vol. 75, no. 4, pp. 769–781, March 2014.zbMATHGoogle Scholar
  6. [6]
    Z. Sun, S.S. Ge and T.H. Lee, “Controllability and reachability criteria for switched linear systems,” Automatica, vol. 38, no. 5, pp. 775–786, May 2002.MathSciNetzbMATHGoogle Scholar
  7. [7]
    M. B. Yazdi and M. R. Jahed-Motlagh, “Stabilization of a CSTR with two arbitrarily switching modes using modal state feedback linearization,” Chemical Engineering Journal, vol. 155, no. 3, pp. 838–843, December 2009.Google Scholar
  8. [8]
    X. L. Zheng, X. D. Zhao, R. Li, and Y. Yin, “Adaptive neural tracking control for a class of switched uncertain nonlinear systems,” Neurocomputing, vol. 168, no. C, pp. 320–326, November 2015.Google Scholar
  9. [9]
    R. Ma and J. Zhao, “Backstepping design for global stabilization of switched nonlinear systems in lower triangular form under arbitrary switchings,” Automatica, vol. 46, no. 11, pp. 1819–1823, November 2010.MathSciNetzbMATHGoogle Scholar
  10. [10]
    Y. F. Wang, C. S. Jiang, and Q. X. Wu, “Attitude tracking control for variable structure near space vehicles based on switched nonlinear systems,” Chinese Journal of Aeronautics, vol. 26, no. 1, pp. 186–193, February 2013.Google Scholar
  11. [11]
    V. Sankaranarayanan and A. D. Mahindrakar, “Switched control of a nonholonomic mobile robot,” Communications in Nonlinear Science & Numerical Simulation, vol. 14, no. 5, pp. 2319–2327, May 2009.MathSciNetzbMATHGoogle Scholar
  12. [12]
    D. Nganga-Kouya and F. A. Okou, “Adaptive backstepping control of a wheeled mobile robot,” IEEE Conf. on Control & Automation, pp. 85–91, 2009.Google Scholar
  13. [13]
    Y. F. Gao, H. Zhang, and Y. H. Ye, “Back-Stepping and neural network control of a mobile robot for curved weld seam tracking,” Procedia Engineering, vol. 15, pp. 38–44, April 2011.Google Scholar
  14. [14]
    Z. P. Wang, S. S. Ge, and T. H. Lee, “Adaptive neural network control of a wheeled mobile robot violating the pure nonholonomic constraint,” IEEE Conf. on Decision & Control, pp. 5198–5203, 2005.Google Scholar
  15. [15]
    N. Hung, J. S. Lm, S. K. Jeong, H. K. Kim, and B. K. Sang, “Design of a sliding mode controller for an automatic guided vehicle and its implementation,” International Journal of Control Automation & Systems, vol. 8, no. 1, pp. 81–90, February 2010.Google Scholar
  16. [16]
    T. Murakami and K. Ohnishi, “Dynamics Identification Method of Multi-Degrees-of-Freedom Robot Based on Disturbance Observer,” Journal of the Robotics Society of Japan, vol. 11, pp. 131–139, January 1993.Google Scholar
  17. [17]
    T. Murakami and K. Ohnishi, “Parameter identification of a direct-drive robot by a disturbance observer,” Advanced Robotics, vol. 7, no. 6, pp. 559–573, January 2012.Google Scholar
  18. [18]
    A. Nikoobin and R. Haghighi, “Lyapunov-based nonlinear disturbance observer for serial n-link robot manipulators,” Journal of Intelligent & Robotic Systems, vol. 55, no. 2, pp. 135–153, July 2009.zbMATHGoogle Scholar
  19. [19]
    X. Zeng, J. Wang, and X. Wang, “Design of sliding mode controller based on SMDO and its application to missile control,” Acta Aeronautica Et Astronautica Sinica, vol. 32, no. 5, pp. 873–880, May 2011.Google Scholar
  20. [20]
    W. H. Chen, D. J. Ballance, P. J. Gawthrop, and J. O’Reilly, “A nonlinear disturbance observer for robotic manipulators,” IEEE Trans. on Industrial Electronics, vol. 47, no. 4, pp. 932–938, August 2000.Google Scholar
  21. [21]
    J. Taghia, X. Wang, S. Lam, and J. Katupitiya, “A sliding mode controller with a nonlinear disturbance observer for a farm vehicle operating in the presence of wheel slip,” Autonomous Robots, vol. 8212, no. 1, pp. 1–18, December 2015.Google Scholar
  22. [22]
    G. P. Shen, C. Q. Wang, and Q. Wang, “Switching motion control of an aircraft skin detection robot with double frames,” Acta Aeronautica Et Astronautica Sinica, vol. 36, no. 6, pp. 2064–2073, June 2015.Google Scholar
  23. [23]
    Y. Wei, J. Qiu, H. R. Karimi, and M. Wang, “Model approximation for two-dimensional Markovian jump systems with state-delays and imperfect mode information,” Multidimensional Systems & Signal Processing, vol. 26, no. 3, pp. 575–597, 2015.MathSciNetzbMATHGoogle Scholar
  24. [24]
    Y. Wei, J. Qiu, and H. R. Karimi, “Quantized H¥ filtering for continuous-time Markovian jump systems with deficient mode information,” Asian Journal of Control, vol. 17, no. 5, pp. 1914–1923, 2015.MathSciNetzbMATHGoogle Scholar
  25. [25]
    M. Chen and J. Yu, “Adaptive dynamic surface control of NSVs with input saturation using a disturbance observer,” Chinese Journal of Aeronautics, vol. 16, no. 3, pp. 853–864, June 2015.Google Scholar
  26. [26]
    Y. Kanayama, “A stable tracking control method for an autonomous mobile robot,” Proc. of IEEE International Conference on Robotics and Automation, pp. 384–389, 1990.Google Scholar
  27. [27]
    L. Vu, D. Chatterjee, and D. Liberzon, “Input-to-state stability of switched systems and switching adaptive control,” Automatica, vol. 43, no. 4, pp. 639–646, April 2007.MathSciNetzbMATHGoogle Scholar
  28. [28]
    A. Levant, “Sliding order and sliding accuracy in sliding mode control,” International Journal of Control, vol. 58, no. 6, pp. 1247–1263, 1993.MathSciNetzbMATHGoogle Scholar
  29. [29]
    J. Davila, L. Fridman, and A. Levant, “Second-order sliding-mode observer for mechanical systems,” IEEE Trans. on Automatic Control, vol. 50, no. 11, November 2005.Google Scholar
  30. [30]
    J. A. Moreno and M. Osorio, “Strict Lyapunov functions for the super-twisting algorithm,” IEEE Trans. on Automatic Control, vol. 57, no. 4, April 2012.Google Scholar
  31. [31]
    Y. Tang, J. A. Fang, M. Xia, and X. Gu, “Synchronization of takagi-sugeno fuzzy stochastic discrete-time complex networks with mixed time-varying delays,” Applied Mathematical Modelling, vol. 34, no. 4, pp. 843–855, 2010.MathSciNetzbMATHGoogle Scholar
  32. [32]
    Y.Wei, J. Qiu, and H. R. Karimi, “Reliable output feedback control of discrete-time fuzzy affine systems with actuator faults,” IEEE Trans. on Circuits & Systems, vol. 64, no. 1, pp. 170–181, 2017.Google Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Congqing Wang
    • 1
  • Junjun Jiang
    • 1
  • Xuewei Wu
    • 1
  • Linfeng Wu
    • 1
  1. 1.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingP. R. China

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