Skip to main content
Log in

A swing constrained time-optimal trajectory planning strategy for double pendulum crane systems

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

In practice, overhead crane systems are widely used and the traditional control methods for a crane system usually treat it as a single pendulum system. However, when the hook mass cannot be ignored or the payload is too large, the crane system may behave more like a double pendulum system, which leads to the fact that traditional control methods are not suitable in this situation. In this paper, we focus on the control problem of a double pendulum crane system and propose a time-optimal trajectory planning method with the consideration of various constraints which can achieve the objectives of both accurate trolley positioning and double pendulum swing suppression. Specifically, the discrete system model is obtained using the discretization technique firstly. Then by deeply analyzing and considering a series of constraints, we formulate a quasiconvex optimization problem. After that, the bisection method is chosen to solve the obtained optimization problem with the corresponding time-optimal trajectory constructed conveniently. A tracking controller is also designed for the double pendulum crane system, which achieves proper trolley tracking performance. At last, both simulation and experimental results are included to illustrate the superior performance of the proposed trajectory planning method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Liu, Y., Yu, H.: A survey of underactuated mechanical systems. IET Control Theory Appl. 7(7), 921–935 (2013)

    Article  MathSciNet  Google Scholar 

  2. Sun, N., Wu, Y., Fang, Y., Chen, H.: Nonlinear stabilization control of multiple-RTAC systems subject to amplitude restricted actuating torques using only angular position feedback. IEEE Trans. Ind. Electron. 64(4), 3084–3094 (2017)

    Article  Google Scholar 

  3. Sun, N., Wu, Y., Fang, Y., Chen, H., Lu, B.: Nonlinear continuous global stabilization control for underactuated RTAC systems: design, analysis, and experimentation. IEEE/ASME Trans. Mechatron. 22(2), 1104–1115 (2017)

    Article  Google Scholar 

  4. Tuan, L., Lee, S.-G., Dang, V.-H., Moon, S., Kim, B.: Partial feedback linearization control of a three-dimensional overhead crane. Int. J. Control Autom. Syst. 11(4), 718–727 (2013)

    Article  Google Scholar 

  5. Tuan, L., Lee, S.-G., Moon, S.-C.: Partial feedback linearization and sliding mode techniques for 2D crane control. Trans. Inst. Meas. Control 36(1), 78–87 (2014)

    Article  Google Scholar 

  6. Zhang, Z., Wu, Y., Huang, J.: Differential-flatness-based finite-time anti-swing control of underactuated crane systems. Nonlinear Dyn. 87(3), 1749–1761 (2017)

    Article  Google Scholar 

  7. Yang, J., Yang, K.: Adaptive coupling control for overhead crane systems. Mechatronics 17(2–3), 143–152 (2007)

    Article  Google Scholar 

  8. Park, M.-S., Chwa, D., Eom, M.: Adaptive sliding-mode antiswing control of uncertain overhead cranes with high-speed hoisting motion. IEEE Trans. Fuzzy Syst. 22(5), 1262–1271 (2014)

    Article  Google Scholar 

  9. Sun, N., Fang, Y., Chen, H.: Adaptive antiswing control for cranes in the presence of rail length constraints and uncertainties. Nonlinear Dyn. 81(1), 41–51 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  10. Sun, N., Fang, Y., Zhang, X.: Energy coupling output feedback control of 4-DOF underactuated cranes with saturated inputs. Automatica 49(5), 1318–1325 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  11. Sun, N., Fang, Y.: New energy analytical results for the regulation of underactuated overhead cranes: an end-effector motion-based approach. IEEE Trans. Ind. Electron. 59(12), 4723–4734 (2012)

    Article  Google Scholar 

  12. Almutairi, N., Zribi, M.: Sliding mode control of a three-dimensional overhead crane. J. Vib. Control 15(11), 1679–1730 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  13. Xi, Z., Hesketh, T.: Discrete time integral sliding mode control for overhead crane with uncertainties. IET Control Theory Appl. 4(10), 2071–2081 (2010)

    Article  MathSciNet  Google Scholar 

  14. Ngo, Q., Hong, K.: Sliding-mode antiswing control of an offshore container crane. IEEE/ASME Trans. Mechatron. 17(2), 201–209 (2012)

    Article  Google Scholar 

  15. Singhose, W., Kim, D., Kenison, M.: Input shaping control of double-pendulum bridge crane oscillations. ASME J. Dyn. Syst. Meas. Control 130(3), 034504.1–034504.7 (2008)

    Article  Google Scholar 

  16. Blackburn, D., Singhose, W., Kitchen, J., Patrangenaru, V., Lawrence, J., Kamoi, T., Taura, A.: Command shaping for nonlinear crane dynamics. J. Vib. Control 16(4), 477–501 (2010)

    Article  MATH  Google Scholar 

  17. Daqaq, M., Masoud, Z.: Nonlinear input-shaping controller for quay-side container cranes. Nonlinear Dyn. 45, 149–170 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  18. Vukov, M., Loock, W., Houska, B., Ferreau, H,. Swevers, J., Diehl, M.: Experimental validation of nonlinear MPC on an overhead crane using automatic code generation. In: Proceedings of American Control Conference, Fairmont Queen Elizabeth, Montral, Canada, pp. 6264–6269 (2012)

  19. Chen, H., Fang, Y., Sun, N.: A swing constraint guaranteed MPC algorithm for underactuated overhead cranes. IEEE/ASME Trans. Mechatron. 21(5), 2543–2555 (2016)

    Article  Google Scholar 

  20. Wu, Z., Xia, X., Zhu, B.: Model predictive control for improving operational efficiency of overhead cranes. Nonlinear Dyn. 79(4), 2639–2657 (2015)

    Article  Google Scholar 

  21. Zhao, Y., Gao, H.: Fuzzy-model-based control of an overhead crane with input delay and actuator saturation. IEEE Trans. Fuzzy Syst. 20(1), 181–186 (2012)

    Article  Google Scholar 

  22. Nakazono, K., Ohnishi, K., Kinjo, H., Yamamoto, T.: Load swing suppression for rotary crane system using direct gradient descent controller optimized by genetic algorithm. Trans. Inst. Syst. Control Inf. Eng. 22(8), 303–310 (2011)

    Google Scholar 

  23. Lee, L., Huang, P., Shih, Y., Chiang, T., Chang, C.: Parallel neural network combined with sliding mode control in overhead crane control system. J. Vib. Control 20, 749–760 (2012)

    Article  Google Scholar 

  24. Lee, H.: Motion planning for three-dimensional overhead cranes with high-speed load hositing. Int. J. Control 78(12), 875–886 (2005)

    Article  MATH  Google Scholar 

  25. Uchiyama, N., Ouyang, H., Sano, S.: Simple rotary crane dynamics modeling and open-loop control for residual load sway suppression by only horizontal boom motion. Mechatronics 23(8), 1223–1236 (2013)

    Article  Google Scholar 

  26. Sun, N., Fang, Y., Zhang, X., Yuan, Y.: Transportation task-oriented trajectory planning for underactuated overhead cranes using geometric analysis. IET Control Theory Appl. 6(10), 1410–1423 (2012)

    Article  MathSciNet  Google Scholar 

  27. Wu, Z., Xia, X.: Optimal motion planning for overhead cranes. IET Control Theory Appl. 8(17), 1833–1842 (2014)

    Article  Google Scholar 

  28. Sun, N., Fang, Y., Zhang, Y., Ma, B.: A novel kinematic coupling-based trajectory planning method for overhead cranes. IEEE/ASME Trans. Mechatron. 17(1), 166–173 (2012)

    Article  Google Scholar 

  29. Chen, H., Fang, Y., Sun, N.: Optimal trajectory planning and tracking control method for overhead cranes. IET Control Theory Appl. 10(6), 692–699 (2016)

  30. Avanço, R.H., Navarro, H.A., Brasil, R.M.L.R.F., Balthazar, J.M., Bueno, Á.M., Tusset, A.M.: Statements on nonlinear dynamics behavior of a pendulum, excited by a crank-shaft-slider mechanism. Meccanica 51, 1301–1320 (2016)

  31. Avanço, R.H., Navarro, H.A., Nabarrete, A., Balthazar, J.M., Tusset, A.M.: Chaotic behavior in the double pendulum under parametric resonance. In: Proceedings of the ASME International Mechanical Engineering Congress and Exposition IMECE2016 (2016)

  32. Vaughan, J., Kim, D., Singhose, W.: Control of tower cranes with double-pendulum payload dynamics. IEEE Trans. Control Syst. Technol. 18(6), 1345–1358 (2010)

    Google Scholar 

  33. Singhose, W., Kim, D.: Manipulation with tower cranes exhibiting double-pendulum oscillations. In: Proceedings of 2007 IEEE International Conference on Robotics and Automation, Roma, Italy, pp. 4550–4555 (2007)

  34. Masoud, Z., Alhazza, K., Abu-Nada, E., Majeed, M.: A hybrid command-shaper for double-pendulum overhead cranes. J. Vib. Control 20(1), 24–37 (2014)

    Article  Google Scholar 

  35. Sun, N., Fang, Y., Qian, Y.: Motion planning for cranes with double pendulum effects subject to state constraints. Control Theory Appl. 31(7), 974–980 (2014). (in Chinese with an English abstract)

    Google Scholar 

  36. Tuan, L., Lee, S.: Sliding mode controls of double-pendulum crane systems. J. Mech. Sci. Technol. 27(6), 1863–1873 (2013)

    Article  Google Scholar 

  37. Sun, N., Fang, Y., Chen, H., Lu, B.: Amplitude-saturated nonlinear output feedback antiswing control for underactuated cranes with double-pendulum cargo dynamics. IEEE Trans. Ind. Electron. 64(3), 2135–2146 (2017)

    Article  Google Scholar 

  38. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambrideg University Press, New York (2004)

    Book  MATH  Google Scholar 

  39. Grant, M., Boyd, S.: CVX: Matlab software for disciplined convex programming, version 2.0 beta. http://cvxr.com/cvx (2013)

  40. Grant, M., Boyd, S.: Graph implementations for nonsmooth convex programs. In: Blondel, V., Boyd, S., Kimura, H. (eds.) Recent Advances in Learning and Control (A Tribute to M. Vidyasagar). Lecture Notes in Control and Information Sciences, pp. 95–110. Springer (2008). http://stanford.edu/~boyd/graph_dcp.html

  41. Makkar, C., Hu, G., Sawyer, W., Dixon, W.: Lyapunov-based tracking control in the presence of uncertain nonlinear parameterizable friction. IEEE Trans. Autom. Control 52(10), 1988–1994 (2007)

    Article  MathSciNet  Google Scholar 

  42. Sun, N., Fang, Y., Chen, H., He, B.: Adaptive nonlinear crane control with load hoisting/lowering and unknown parameters: design and experiments. IEEE/ASME Trans. Mechatron. 20(5), 2107–2119 (2015)

    Article  Google Scholar 

  43. Huang, C., Wang, W., Chiu, C.: Design and implementation of fuzzy control on a two-wheel inverted pendulum. IEEE Trans. Ind. Electron. 58(7), 2988–3001 (2011)

    Article  Google Scholar 

  44. Herisse, B., Hame, T., Mahony, R., Russotto, F.: Landing a VTOL unmanned aerial vehicle on a moving platform using optical flow. IEEE Trans. Robot. 28(1), 77–89 (2012)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under Grant 61503200, in part by the Natural Science Foundation of Tianjin under Grant 15JCQNJC03800, and in part by the National Science Fund for Distinguished Young Scholars of China under Grant 61325017.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yongchun Fang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, H., Fang, Y. & Sun, N. A swing constrained time-optimal trajectory planning strategy for double pendulum crane systems. Nonlinear Dyn 89, 1513–1524 (2017). https://doi.org/10.1007/s11071-017-3531-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-017-3531-0

Keywords

Navigation