Motion tracking control of actuator in the active-truncated model test of deep-water mooring system

Abstract

The motion of truncated point in the active-truncated model test of deep-water mooring system can be simulated using the actuator, and the motion tracking control of actuator determines the validity of test results. Taking the Stewart Platform as actuator, the kinematic model is established. The permanent magnet synchronous motor (PMSM) is selected as the drive motor of actuator, and the transfer function is identified using the white noise signal excitation. The Feedforward control and RBF neural network control methods are designed to compare the motion tracking control effect at the truncated point and the corresponding influences on the top tension at the fairlead. The simulation results show that the feedforward control can reduce the motion tracking error by 50% while the RBF neural network can reduce the tracking error by 75%, which both have obvious effect on the motion tracking control and provide theoretical basis for constructing the active-truncated model test platform of deep-water mooring system.