Nonlinear Dynamics

, Volume 81, Issue 1–2, pp 41–51 | Cite as

Adaptive antiswing control for cranes in the presence of rail length constraints and uncertainties

  • Ning Sun
  • Yongchun Fang
  • He Chen
Original Paper


In practical applications, crane systems usually suffer from unfavorable factors, such as parametric uncertainties consisting of unknown friction forces, trolley mass, payload mass, and wire length. Moreover, existing crane control methods cannot guarantee the motion scope of the trolley, since merely asymptotic results, at best, can be obtained because of the nonlinear underactuated nature. Due to unexpected overshoots, existing methods, unless well tuned, may drive the trolley to go beyond the scope of the rail. In this paper, we consider the control problem for underactuated crane systems by considering the aforementioned two points and present an adaptive nonlinear control law. The control framework is established by total energy shaping, and a novel additional term is introduced into the controller to prevent the trolley from running out of the permitted range. We employ Lyapunov-based analysis to prove that the equilibria of the closed-loop system is asymptotically stable. Hardware experimental results are included to suggest that the proposed method achieves increased control performance vis-à-vis existing methods and admits strong robustness with regard to uncertainties and external disturbances, while ensuring the trolley motion range limitation.


Underactuated crane systems Rail length constraints  Antiswing control Uncertainties 



The authors would like to express their sincere thanks to the reviewers and editors for their constructive comments/suggestions, which have greatly improved the quality of the paper. They also acknowledge the financial supports from the National Science and Technology Pillar Program of China (Grant No. 2013BAF07B03), the National Science Fund for Distinguished Young Scholars of China (Grant No. 61325017), the Natural Science Foundation of Tianjin, and the National Natural Science Foundation of China (Grant No. 11372144).


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Institute of Robotics and Automatic Information System (IRAIS) and The Tianjin Key Laboratory of Intelligent Robotics (tjKLIR)Nankai UniversityTianjinChina

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