Container Crane Smart Anti-sway Control System And Simulation

With the global economic development, more and more material transit equipment are used in production process. Sea transportation take a large proportion in the whole international material transit system, and port container cranes play an important role in the sea transportation. So the important aspect what we should research is how to increase the productivity of port container cranes. The most important factor influencing the efficiency of port container cranes is the oscillations of the payload on cranes. Then eliminating and controlling the swaying of loads is very important for increasing the work efficiency of cranes as well as decreasing safety hazard during loading & unloading operation.The status of research about anti-sway control of container crane is expatiated in this thesis. On the base of analyzing the physical model of container crane, a nonlinear mathematical model is set up, and a nonlinear simulink model based on the mathematical model is constructed, which offers a foundation for the further controller design.In this paper, a two closed-loop PID controller is firstly designed based on the nonlinear model by the feedback of position and angel. The parameter of PID controller can be optimized by the NCD block, and besides, the NCD block can permit the parameter of system variable in a certain range when optimizing.Due to being many unpredictable disturb when the crane running, it's difficult and even unrealized to construct a accurate model to reflect the crane's dynamic process. In order to control the oscillation more exactly and even eliminating the swaying influence, this paper simulate the dynamic behaviors of the crane system based on simulink simulate system, and summarizes the influence results of the dynamic performance of the crane with different kind of parameter setting. Then a crane nonlinear system controller is designed utilizing input shaping technique. And discusses the performance of the designed controller based on simulink simulation result. Through observing the outcome of the control system we can conclude: the two controller can make the crane pack accurately at the destination and eliminate payload oscillation at the same time, the performance is satisfactory, moreover, the two control system has better robust when the mass of load and the length of rope changing. The simulink experiment can prove that the two controllers are effective and practical.