Crane Intelligent Anti-sway Control Method Study

For the crane system, this paper reviews the domestic and international present status of anti-swing control of crane, and presents the background and significance of topic selection. Several new intelligent anti-swing control schemes are proposed according to the characteristics and shortages of the existed control schemes. Major works are listed as follows:Firstly, the mechanical analysis of the crane system is presented, three-dimensional, two-dimensional mathematical model with/without promotion of crane are derived based on Lagrange theorem. The linear model is obtained by linearizing two-dimensional mathematical model of crane without promotion of the load.Secondly, a fuzzy control scheme based on genetic algorithm is proposed for the crane system. Fuzzy position controller and fuzzy anti-swing controller are designed. In the control scheme, genetic algorithm is used to optimize membership functions, quantization factors and scale factors, which enhances the self-adaptive ability of fuzzy control and improves control performance of system.Thirdly, a hybrid control scheme is presented to achieve the crane anti-swing. Hierarchical sliding mode controller is designed to control trolley position and load swing. Zero vibration and zero vibration derivative time delay filter are designed to further reduce residual vibration of the load. Simulation results on the crane system prove the effectiveness and good dynamic performance and robustness are obtained.Fourthly, based on neural network, a fuzzy sliding mode control scheme is developed. The fuzzy sliding mode controller is deduced to implement the precise positioning and anti-swing ability of the crane system. In order to overcome the uncertainty problem of load changes and external disturbance, the uncertainties of crane model are approximated by a RBF neural network.Finally, three control schemes are simulated. Simulation results show the effectiveness and feasibility.