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A GPC-based Multi-variable PID Control Algorithm and Its Application in Anti-swing Control and Accurate Positioning Control for Bridge Cranes

  • Control Theory and Applications
  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

It is one of the key tasks for the bridge crane to achieve anti-swing control of the hook and the accurate positioning of the body to work efficiently, safely and automatically. Based on Lagrange equation, this paper is to propose a dynamic model of the crane motion system for designing controller. In the controller design, Proportional-Integral-Derivative (PID), the most widely used controller in engineering, is adopted and a new parameter tuning algorithm for a multi-variable PID controller based on generalized predictive control (GPC) is given. It is found that the multi-variable PID controller shares the same structural mathematical expressions with the GPC law, which makes for the transfer and calculation of the three parameters P, I and D, and that the new algorithm enables the traditional PID controller to perform as brilliantly as the GPC. The results of both the simulation and real-time control experiments show that the newly-proposed PID controller can effectively eliminate the swing of the hook and control the bridge cranes moving position accurately.

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Authors and Affiliations

  1. School of Information Science and Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan, 430080, China

    Bin Yang, Zhen-Xing Liu, Hui-Kang Liu & Sen Lin

  2. Engineering and Technical College of Chengdu University of Technology, 222 Xiaoba Road, Leshan, 614000, China

    Bin Yang & Yan Li

Authors
  1. Bin Yang
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  2. Zhen-Xing Liu
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  3. Hui-Kang Liu
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  4. Yan Li
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Correspondence to Bin Yang.

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Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Yang Tang under the direction of Editor Hamid Reza Karimi. This work is supported by the National Natural Science Foundation of China (Grant no. 61174107) and the National Key R&D Program of China (Grant no. 2017YFC0805100).

Bin Yang received his master’s degree in control theory and control engineering from Wuhan University of science and technology, China, in 2007. He is studying for a Ph.D. in control science and engineering at Wuhan University of science and technology, China, and he is a associate professor at the Engineering and Technical College of Chengdu University of Technology, China. His research interests include intelligent control, system identification based on deep learning, and plasma configuration control in tokamak experiments.

Zhen-Xing Liu received his doctorate from Huazhong University of science and technology, China, in 2004. He is a professor and doctoral supervisor of School of information science and engineering, Wuhan University of science and technology, China. His research interests include advanced control theory and its application, new electric drive, and equipment fault diagnosis.

Hui-Kang Liu received his master’s degree in control theory and control engineering from Wuhan University of science and technology, China, in 1988. He is a professor and doctoral supervisor of School of information science and engineering, Wuhan University of science and technology, China. His research interests include intelligent equipment, new electric drive, equipment fault diagnosis.

Yan Li received her M.A. degree in English Literature and Linguistics from Beijing Foreign Language Studies University, China, in 2006 and has been promoted to the rank of associate professor since 2016. Her research interests include corpus-based translation, English literature and foreign language acquisition.

Sen Lin received his master’s degree in control theory and control engineering from Wuhan University of science and technology, China, in 2007. Now, he is studying for a Ph.D. in control science and engineering at Wuhan University of science and technology, China. His research interests include intelligent control, new electric drive, equipment fault diagnosis.

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Yang, B., Liu, ZX., Liu, HK. et al. A GPC-based Multi-variable PID Control Algorithm and Its Application in Anti-swing Control and Accurate Positioning Control for Bridge Cranes. Int. J. Control Autom. Syst. 18, 2522–2533 (2020). https://doi.org/10.1007/s12555-019-0400-2

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  • DOI: https://doi.org/10.1007/s12555-019-0400-2

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