Design Robust Controllers of Convey-Crane System under Different Types of Uncertainty

Abstract

In this paper, the designing of robust controllers for well-known convey crane systems in the presence of uncertainties is presented. Cranes play a great role in the industrial environment, construction sites, ship-yard, and rial-yard because of their efficiency and accuracy in moving heavy and dangerous materials from one loading location to another. The main challenge in controlling such kinds of systems is to minimize the undesirable swings when different payloads are carried. This phenomenon is because the convey crane is classified as an under actuated nonlinear system and there are many sources of uncertainties that affect the plant of the physical system Hence, the stability of the convey crane system in the presence of the uncertainties became a challenging task between the researchers in the control engineering field and used as a benchmark in universities. In this research, firstly, the stability of the linearized model of the convey-crane system is analyzed using the edge theorem in the presence of two uncertain parameters: the rope length and the weight of the load, where the classical pole placement technique is used for stabilization purposes. Secondly, the sliding mode control (SMC) is proposed in order to stabilize the nonlinear model of the convey-crane system with the presence of noise signals. In order to test the effectiveness of the proposed SMC controller, a conventional PID control is applied to the linearized model of the convey-crane system, where the PID parameters are tuned using the well-known Ziegler-Nicholas method. The robustness against the uncertainties in the parameters of the convey crane is achieved by using the Edge theorem, whereas the robustness against the noise signal is tested by using MATLAB; the simulation results show the superiority of the SMC controller over the PID.

Country : Palestine

1 Mustafa M. Abu Abedallah2 Moayed Almobaied3 Hassan S. Al-Nahhal

  1. Electrical Engineering Department, Islamic University of Gaza, Gaza, Palestine
  2. Electrical Engineering Department, Islamic University of Gaza, Gaza, Palestine
  3. Electrical Engineering Department, Islamic University of Gaza, Gaza, Palestine

IRJIET, Volume 7, Issue 8, August 2023 pp. 88-100

doi.org/10.47001/IRJIET/2023.708012

References

  1. Eihab M Abdel-Rahman, Ali H Nayfeh, and Ziyad N Masoud. Dynamics and control of cranes: A review. Journal of Vibration and control, 9(7):863–908, 2003.
  2. Ju¨rgen Ackermann, Andrew Bartlett, Dieter Kaesbauer, Wolfgang Sienel, and Reinhold Steinhauser. Robust control: Systems with uncertain physical parameters. Springer, 1993.
  3. Ju¨rgen Ackermann, Paul Blue, Tilman Bu¨nte, L Gu¨venc, Dieter Kaesbauer, Michael Kordt, Michael Muhler, and Dirk Odenthal. Robust control: the parameter space approach, volume 2. Springer, 2002.
  4. Charles Aguiar, Daniel Leite, Daniel Pereira, Goran Andonovski, and Igor Skrjanc. Non-ˇ linear modeling and robust lmi fuzzy control of overhead crane systems. Journal of the Franklin Institute, 358(2):1376–1402, 2021.
  5. Naif B Almutairi and Mohamed Zribi. Sliding mode control of a three-dimensional overhead crane. Journal of vibration and control, 15(11):1679–1730, 2009.
  6. Giorgio Bartolini, Alessandro Pisano, and Elio Usai. Second-order sliding-mode control of container cranes. Automatica, 38(10):1783–1790, 2002.
  7. A Benhidjeb and GL Gissinger. Fuzzy control of an overhead crane performance comparison with classic control. Control Engineering Practice, 3(12):1687–1696, 1995.
  8. J. Collado, R. Lozano, and I. Fantoni. Control of convey-crane based on passivity. In Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), volume 2, pages 1260–1264 vol.2, 2000.
  9. Sami Ud Din, Qudrat Khan, Fazal-Ur Rehman, and Rini Akmeliawanti. A comparative experimental study of robust sliding mode control strategies for underactuated systems. IEEE Access, 5:10068–10080, 2017.
  10. Sam Chau Duong, Eiho Uezato, Hiroshi Kinjo, and Tetsuhiko Yamamoto. A hybrid evolutionary algorithm for recurrent neural network control of a three-dimensional tower crane. Automation in Construction, 23:55–63, 2012.
  11. Taha Elmokadem, Mohamed Zribi, and Kamal Youcef-Toumi. Trajectory tracking sliding mode control of underactuated auvs. Nonlinear Dynamics, 84(2):1079–1091, 2016.
  12. Isabelle Fantoni, Rogelio Lozano, and Rogelio Lozano. Non-linear control for underactuated mechanical systems. Springer Science & Business Media, 2002.
  13. Huiru Guo, Zhi-Yong Feng, and Jinhua She. Discrete-time multivariable pid controller design with application to an overhead crane. International Journal of Systems Science, 51(14):2733–2745, 2020.
  14. Hazriq Izzuan Jaafar, Z Mohamed, Amar Faiz Zainal Abidin, and Z Ab Ghani. Pso-tuned pid controller for a nonlinear gantry crane system. In 2012 IEEE International Conference on Control System, Computing and Engineering, pages 515–519. IEEE, 2012.
  15. Gyoung-Hahn Kim and Keum-Shik Hong. Adaptive sliding-mode control of an offshore container crane with unknown disturbances. IEEE/ASME Transactions on Mechatronics, 24(6):2850–2861, 2019.
  16. Ho-Hoon Lee. Modeling and control of a three-dimensional overhead crane. 1998.
  17. Lun-Hui Lee, Pei-Hsiang Huang, Yu-Cheng Shih, Tung-Chien Chiang, and Cheng-Yuan Chang. Parallel neural network combined with sliding mode control in overhead crane control system. Journal of Vibration and Control, 20(5):749–760, 2014.
  18. Javier Moreno-Valenzuela and Carlos Aguilar-Avelar. Motion control of underactuated mechanical systems, volume 1. Springer, 2018.
  19. Quang Hieu Ngo, Ngo Phong Nguyen, Chi Ngon Nguyen, Thanh Hung Tran, and Quang Phuc Ha. Fuzzy sliding mode control of an offshore container crane. Ocean Engineering, 140:125–134, 2017.
  20. Reza Olfati-Saber. Nonlinear control of underactuated mechanical systems with application to robotics and aerospace vehicles. PhD thesis, Massachusetts Institute of Technology, 2001.
  21. Pathan Shabnam, AK Priyanka, T Vijay Muni, and S Rajasekhar. Pid controller based grid connected wind turbine energy system for power quality improvement. Journal of Critical Reviews, 7(7):31–35, 2020.
  22. Le Anh Tuan and Soon-Geul Lee. Sliding mode controls of double-pendulum crane systems. Journal of Mechanical Science and Technology, 27(6):1863–1873, 2013.
  23. Le Anh Tuan, Sang-Chan Moon, Won Gu Lee, and Soon-Geul Lee. Adaptive sliding mode control of overhead cranes with varying cable length. Journal of Mechanical Science and Technology, 27(3):885–893, 2013.
  24. Xianqing Wu, Kexin Xu, Meizhen Lei, and Xiongxiong He. Disturbance-compensation based continuous sliding mode control for overhead cranes with disturbances. IEEE Transactions on Automation Science and Engineering, 17(4):2182–2189, 2020.
  25. Jian-Xin Xu, Zhao-Qin Guo, and Tong Heng Lee. Design and implementation of integral sliding-mode control on an underactuated two-wheeled mobile robot. IEEE Transactions on industrial electronics, 61(7):3671–3681, 2013.
  26. Jung Hua Yang and Kuang Shine Yang. Adaptive coupling control for overhead crane systems. Mechatronics, 17(2-3):143–152, 2007.
  27. Wen Yu, Xiaoou Li, and Francisco Panuncio. Stable neural pid anti-swing control for an overhead crane. Intelligent Automation & Soft Computing, 20(2):145–158, 2014.
  28. Menghua Zhang, Xin Ma, Rui Song, Xuewen Rong, Guohui Tian, Xincheng Tian, and Yibin Li. Adaptive proportional-derivative sliding mode control law with improved transient performance for underactuated overhead crane systems. IEEE/CAA Journal of Automatica Sinica, 5(3):683–690, 2018.
  29. Network lifetime through an integrated model for clustering and routing in wireless sensor networks,” Comput. Netw., vol. 55, no. 13, pp. 2803–2820, Sep. 2011.