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Journal of Applied Nonlinear Dynamics 10(2) (2021) 197--209 | DOI:10.5890/JAND.2021.06.001

Bilal H. Abduljabbar$^{1,2}$, John Billingsley$^{1}$

$^{1}$ School of Mechanical and Electrical Engineering University of Southern Queensland, West Street, Darling Heights, Toowoomba, Queensland, Australia

$^{2}$ Department of Mechanical, College of Engineering, University of Al-Anbar, Al-Anbar, Iraq

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Abstract

Tower crane systems are commonly used at construction sites. The need to damp the swinging of the load presents a task requiring great skill for manual control. This has led earlier researchers to apply elaborate control strategies. In this paper, we propose the use of a 'pragmatic' paradigm to define a system that can move the load to the desired target with little or no swing. The essence of pragmatic control is gleaned from autopilot designs of half a century ago. The control is designed as a set of 'nested loops'. The error in an outer loop defines a demand value for the next inner loop, so for example the load position error defines a corrective velocity. In each case the demand is subjected to a limit. This is continued through each layer until the innermost loop, which might take the form of a velocity loop wrapped around a motor to give crisp velocity control. The dynamic model is derived as a state space representation. The proposed strategy was tested by MATLAB which showed that the strategy is successful and effective to control a tower crane system and suppress the load swing. Comparisons are made between the performance of this simples control strategy and that of the complex published alternatives.

References

1. [1]	Golafshani, A.R. (1999), Modeling and optimal control of tower crane motions.

2. [2]	Al-Mousa, A.A., Nayfeh, A.H., and Kachroo, P. (2003), Control of rotary cranes using fuzzy logic, Shock and Vibration, 10(2), 81-95.

3. [3]	Omar, H.M. and Nayfeh, A.H. (2003), Gain scheduling feedback control for tower cranes, Modal Analysis, 9(3-4), 399-418.

4. [4]	Lew, J.Y. and Khalil, A. (2000, June), Anti-swing control of a suspended load with a robotic crane, In~Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No. 00CH36334)~(Vol. 2, pp. 1042-1046). IEEE.

5. [5]	Lew, J.Y. and Halder, B. (2003, June), Experimental study of anti-swing crane control for a varying load. In~Proceedings of the 2003 American Control Conference, 2003.~(Vol. 2, pp. 1434-1439). IEEE.

6. [6]

   Sadati, N. and Hooshmand, A. (2006, November), Design of a gain-scheduling anti-swing controller for tower cranes using fuzzy clustering techniques. In~2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA06)~(pp. 172-172). IEEE.

7. [7]	Ju, F., Choo, Y.S., and Cui, F.S. (2006), Dynamic response of tower crane induced by the pendulum motion of the payload, International Journal of Solids and Structures, 43(2), 376-389.

8. [8]	Singhose, W. and Kim, D. (2007, April). Manipulation with tower cranes exhibiting double-pendulum oscillations. In~Proceedings 2007 IEEE International Conference on Robotics and Automation~(pp. 4550-4555). IEEE.

9. [9]	Rubio-Avila, J.J., Alcantara-Ramirez, R., Jaimes-Ponce, J., and Siller-Alcal\{a}, I.I. (2007), Design, construction, and control of a novel tower crane, International journal of mathematics and computers in simulation, 1(2).

10. [10]

    Avila, J.R., Alc\{a}ntara-Ram\{\i}rez, R., Jaimes-ponce, J., and Siller-Alcal\{a}, I.I. (2008, January), Design of a self-balancing tower crane. In~Proceedings of the 2nd WSEAS International Conference on Circuits, Systems, Signal and Telecommunications~(pp. 109-115). World Scientific and Engineering Academy and Society (WSEAS).

11. [11]	B\"{o}ck, M. and Kugi, A. (2013), Real-time nonlinear model predictive path-following control of a laboratory tower crane, IEEE Transactions on Control Systems Technology, 22(4), 1461-1473.

12. [12]	Breuning, P. (2015), Linear Model Predictive Control of a 3D Tower Crane for Educational Use (Doctoral dissertation, University of Stuttgart).

13. [13]	Matu\v{s}ko, J., Ile\v{s}, \v{S}., Koloni\{c}, F., and Le\v{s}i\{c} V. (2015), Control of 3D tower crane based on tensor product model transformation with neural friction compensation, Asian Journal of Control, 17(2), 443-458.

14. [14]	Wu, T.S., Karkoub, M., Yu, W.S., Chen, C.T., Her, M.G., and Wu, K.W. (2016), Anti-sway tracking control of tower cranes with delayed uncertainty using a robust adaptive fuzzy control, Fuzzy Sets and Systems, 290, 118-137.

15. [15]	Alhassan, A., Mohamed, Z., Abdullahi, A.M., Bature, A.A., Haruna, A., and Tahir, N.M. (2018), Input Shaping Techniques for Sway Control of a Rotary Crane System, Jurnal Teknologi, 80(1).

16. [16]	Sun, N., Fang, Y., Chen, H., Lu, B., and Fu, Y. (2016), Slew/translation positioning and swing suppression for 4-DOF tower cranes with parametric uncertainties: Design and hardware experimentation.~IEEE Transactions on Industrial Electronics, 63(10), 6407-6418.

17. [17]	Vaughan, J., Kim, D., and Singhose, W. (2010), Control of tower cranes with double-pendulum payload dynamics, IEEE Transactions on Control Systems Technology, 18(6), 1345-1358.

18. [18]	Samin, R.E., Mohamed, Z., Jalani, J., and Ghazali, R. (2013, December), A hybrid controller for control of a 3-DOF rotary crane system. In~2013 1st International Conference on Artificial Intelligence, Modelling and Simulation~(pp. 190-195). IEEE.

19. [19]	Win, T.M. (2016), Robotic Tower Crane Modelling Control (RTCMC) (Doctoral dissertation, The University of New South Wales).

20. [20]	Graichen, K., Egretzberger, M., and Kugi, A. (2010), Suboptimal model predictive control of a laboratory cranem IFAC Proceedings Volumes, 43(14), 397-402.

21. [21]

    Bari\v{s}a, T., Bartulovi\{c}, M., \v{Z}u\v{z}i\{c}, G., Ile\v{s}, \v{S}., Matu\v{s}ko, J., and Koloni\{c}, F. (2014, September), Nonlinear predictive control of a tower crane using reference shaping approach, In~2014 16th International Power Electronics and Motion Control Conference and Exposition~(pp. 872-876). IEEE.

22. [22]	Tinkir, M., \"{O}nen, \"{U}., Kalyoncu, M., and \c{S}ah, Y. (2011, March), Modeling and control of scaled a tower crane system, In~2011 3rd International Conference on Computer Research and Development (Vol. 4, pp. 93-98). IEEE.

23. [23]	Duong, S.C., Uezato, E., Kinjo, H., and Yamamoto, T. (2012), A hybrid evolutionary algorithm for recurrent neural network control of a three-dimensional tower crane, Automation in Construction, 23, 55-63.

24. [24]	Al-Mousa, A.A. (2000), Control of rotary cranes using fuzzy logic and time-delayed position feedback control, (Doctoral dissertation, Virginia Tech).