Research On Control Method Of Bridge Crane System

Bridge crane is a transportation system widely used in large cargo handling places.Because the hook and load of the bridge crane are connected by the lifting rope,the swing phenomenon will occur when it is disturbed,which will affect the positioning accuracy of the bridge crane.The anti-swing of the load required a lot of time,which affects the work efficiency and is also easy to cause safety hazards.Therefore,it is of great significance to study how to realize the rapid positioning of the bridge crane and eliminate the swing of the load in a short time.Therefore,this paper mainly carried out the following work for anti-swing and positioning control of bridge crane:After analyzing the movement mode of the bridge crane system,this paper selects the way of separate movement of the trolley and the bridge to control.The mechanical structure of the bridge crane was analyzed to obtain a reasonable simplified model.The mathematical model and simplified linear model of two-dimensional and three-dimensional bridge crane were established by Lagrange modeling method.On this basis,the system performance was analyzed.It laid the foundation for subsequent research.Aiming at the problem of anti-swing and positioning control of bridge crane and the inaccuracy of model caused by ignoring some secondary factors due to model simplification,a sliding mode variable structure controller based on decoupling algorithm was designed.Firstly,the decoupling algorithm was used to remove the coupling of the model,and the sliding mode variable structure controller was established according to the decoupled model.The Lyapunov stability criterion was used to prove the asymptotic stability of the system,and the performance of the system was verified by simulation experiments.On this basis,the control of the bridge crane by the actual operator was simulated.The simulation result shown that the control algorithm has good performance.The above model uses a linearized model.When the linearized model was subjected to large interference,the linearization condition cannot be guaranteed.The RBF neural network was introduced to approach the uncertainty of the nonlinear model,and the weights of the RBF neural network were updated by the adaptive law.An adaptive sliding mode controller based on RBF neural network was designed in the framework of sliding mode control.The asymptotic stability of the system was proved by Lyapunov stability criterion,and the performance of the system was verified by simulation experiments.The above two algorithms simulate the same actual operation and compare the simulation results.The simulation results shown that the control effect of RBF neural network adaptive sliding mode control was slightly better for anti-swing and positioning control of bridge crane.For load increase,the sliding mode variable structure control was slightly better.