Research On Reducing Resonance Based On Positioning And Eliminating Swing Control Of Bridge Crane

Bridge crane is a kind of widely used machinery,which is used to lift heavy objects.For the bridge crane,the most important problem to be solved is how to prevent the weight swing.Compared with solids,when the lifted heavy object is high-temperature molten metal,its center of gravity will change with the swing.At the same time,in order to eliminate the swing,the control mechanism needs to adjust the control amount repeatedly,which will cause the resonance between the lifted metal and the lifted steel wire rope,and then the molten metal will spill out of the container and cause safety accidents.Therefore,it is necessary to eliminate the resonance caused by the crane operation when the lifting weight is high temperature molten metal.In this paper,firstly,the dynamic characteristics of the bridge crane are analyzed.According to the mechanism modeling method,the linear and nonlinear equations of the bridge crane are established by Lagrange equation,and the simulated liquid interference is added.Combined with the mathematical model of the bridge crane,a sliding mode controller with good control effect is introduced,and a notch filter is added between the control mechanism and the crane model to suppress the resonance disturbance.After the initial parameter setting,the resonance disturbance is reduced.In order to further reduce the resonance amplitude,a neural network algorithm is introduced to optimize the parameters of the notch filter.The results show that the performance of the notch filter is further improved.As the initial parameters of the notch filter are selected and adjusted based on experience,and its accuracy is limited.Particle swarm optimization algorithm is added to optimize and simulate it.The simulation results show that the neural network notch filter optimized by PSO has better filtering performance.