Design And Simulation Of Anti-swing System For Overhead Crane

With the rapid development of modern logistics transportation industry,the demand of bridge crane for logistics transshipment is increasing.Because the bridge crane mainly uses wire rope to lift containers,it is easy to be affected by sea breeze,external vibration,inertia caused by the traveling process of the trolley and other factors,which leads to the deviation of containers from the vertical direction and affects the efficiency and accuracy of the bridge crane.At present,some mechanical anti-swing mechanisms are used to correct the deviation of overhead crane.These anti-swing devices have some disadvantages,such as complex structure,low work efficiency,high processing and manufacturing costs,and their application scope is limited in many occasions.Firstly,the crane system was modeled and analyzed.Through two-dimensional and three-dimensional modeling of overhead crane,the dynamic model and mathematical model of overhead crane were established respectively,and the characteristics of the crane system model were analyzed.According to the transfer function of the bridge crane,the Simulink model of the system was established,and then the closed-loop controller of the system was established.The controller was simulated and analyzed by mathematical software.Finally,the best performance of the PID controller was selected.However,the former PID controller had some shortcomings such as poor anti-interference ability,so the fuzzy logic control method was used to design the PID controller,and then the FPID controller was designed.Through the simulation of the FPID controller,it can be concluded that the FPID controller was superior to the PID controller in the positioning accuracy and swing control of the crane,and the change of its own parameters will not affect the whole system.The optimal design of the FPID controller was carried out by using the neural network algorithm and the particle swarm optimization algorithm,and the advantages and disadvantages of the particle swarm optimization algorithm and the genetic algorithm were obtained through comparative analysis.Then the optimal design of the FPID controller was carried out by using the particle swarm optimization algorithm.Finally,the designed FPID controller was simulated by finite element method.The optimized FPID controller could reduce the swing angle of the system and make the system achieve stable time quickly.