Neural network based decoupling control of lifting of 7500t floating crane vessel

Abstract

According to characteristics of nonlinear and strong coupling between rolling and luffing of 7500 Ton crane arm with vessel stability in lifting process, we built a mathematical model of movement stance of crane vessel lifting process and brought forward a neural network decoupling control strategy. The control method was applied to solve the coupling problem between rolling and luffing for the crane lifting of the vessel. The executive motors of crane vessel work stably under the control. The space position of heavy load can be controlled stably in lifting process because of good control stability of motor. The control is also well effect for vessel stability. The control aim is used for safety and reliability of crane vessel operation. Simulation results indicate that there is good stability of dynamic decoupling between rolling and luffing of crane vessel.