巨型浮吊起重船稳性安全的解耦控制方法

针对巨型起重船起重臂相对船体进行起吊、回转、变幅运动存在非线性强耦合等问题,在建立了起重船运动姿态数学模型的基础上,提出一种神经网络解耦控制策略。应用神经网络自适应解耦反馈控制方法,实现起重机回转、变幅的解耦,最终控制起吊执行电机、船舶压载泵及锚泊定位电机,将起重船起重过程的船舶重心控制在稳定区域内,从而使起重船的操控安全高效。仿真结果表明,起重机的回转和变幅运动的动态解耦控制效果良好。

Decoupling Control Method for Stability and Safety of Giant Floating Crane Vessel

In view of non-linear strong coupling problems occurring in hoisting, slewing and luffing movements of the lifting arm relative to the hull of giant floating crane vessel, this paper puts forward a neural network decoupling control strategy by establishing movement atti- tude mathematical model of crane vessel. The adaptive neural network decoupling feedback con- trol method has been applied to realize the decoupling of slewing and luffing movements of crane and finally control the lifting executive motor, ship ballast pump and mooring position motor. The gravity center of crane vessel in lifting process is controlled within a stable region, so that the vessel can be controlled safely and effectively. The simulation result shows that the dynamic decoupling control of crane in slewing and luffing movements has good effect.