A GPC-based Multi-variable PID Control Algorithm and Its Application in Anti-swing Control and Accurate Positioning Cont
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ISSN:1598-6446 eISSN:2005-4092 http://www.springer.com/12555
A GPC-based Multi-variable PID Control Algorithm and Its Application in Anti-swing Control and Accurate Positioning Control for Bridge Cranes Bin Yang*, Zhen-Xing Liu, Hui-Kang Liu, Yan Li, and Sen Lin 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, ProportionalIntegral-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. Keywords: Anti-swing control, bridge crane, generalized predictive control, multivariable PID controller.
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INTRODUCTION
The bridge crane is widely used in industrial and mining enterprises, stations, ports, and warehouses. In general, it is operated manually by highly-trained skilled workers to start, stop, move back and forth, lift and so on. And due to inertia, wind resistance, and friction, the hook of the bridge crane usually swings in operation, which renders a great difficulty for a skilled worker, for he must stop the crane accurately and prevent the hook from swinging at the same time, and by doing so, various safety problems will arise and the work efficiency of the bridge crane also will decrease. Therefore, many experts have been focusing on how to achieve the anti-swing control of the hook and the accurate positioning of the crane body and attained fruitful achievements in recent years. For example, an improved differential evolution (DE) algorithm was proposed, which was used to optimize and tune the PID parameters off-line [1]. The DE-based PID controller can eliminate the swing of the hook and position the crane accurately to a certain degree. However, it could be seen from the simulation results of the algorithm that the controller suppressed the swing of the hook a little too long,
so it cannot achieve a satisfactory anti-swing effect. More importantly, the algorithm was not verified by the actual control experiments. We can also see that by constructing Lyapunov functions, a direct design for the controller is proposed and verified to be feasible by experiments [2]. However, it is well known that constructing a suitable Lyapunov function is not easy. In [3], a PFPSO
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