Bridge Crane Position Tracking And Anti-swing Control Research Based On Iterative Learning

Bridge crane is the main means of transport in ports, docks, freight yard and other places. The crane lifting speed, walking speed and accurate positioning of goods have a direct impact on the production efficiency and safety issues. Positioning and anti-swing control of crane are two hot issues of the research. According to statistics, each time when traditional crane loading and unloading the goods, more than 30% of the time wasted on a fixed point on average. This affects the production efficiency seriously and causes potential safety hazard. So the precise positioning and anti-swing control research of bridge crane has important significance.The research status at home and abroad on this issue has been summarized. A variety of intelligent control, mechanical control methods are analyzed and discussed. There are some successful application cases but the positioning accuracy and control effect is not satisfactory so far.Bridge crane has strong repeatability when transport the same batch of goods in quantity. Repeatability embodied in the same starting point and end point, the same desired trajectory and the same load. In view of the repeatability of bridge crane, this thesis researches the positioning control and anti-swing control based on the ILC. Frist, establishing simplified physical model of bridge crane,then getting the dynamic equation from analyzing the stress of car and load. Second, through the dynamic equation we can get 2 d and 3 d nonlinear mathematical model of bridge crane based on the Lagrange’s equations. The mathematical model has been linearized. The ILC controller for 2 d and 3 d bridge crane when rope length is changed or fixed has been designed respectively. The ILC controller for bridge crane when fixed initial error is existed is also designed. The convergence of the algorithm has been proved in theory. It can be proved that the ILC controller can restrain the pendulum angle effectively and track location completely in a limited time. The car arrived at the specified location in the designated time, reached the expected aim.