Sliding Mode Control of Overhead Crane Based on RBF Neural Network

Aiming at the problems of trolley positioning and load anti-swing of bridge crane, the controller was designed in the framework of sliding mode control, and RBF neural network was introduced to solve the uncertainty of the bridge crane model. The stability of the designed control system was determined by using LaSalle invariance theorem. The simulation experiments of the controller were realized with MATLAB software. The experimental results shown that the presented control method can realize the rapid positioning of trolley and bridge and the load anti-swing, and has a good control effect.