Research On The Longitudinal Motion Control Of SWATH Based On QFT

The Small-Waterplane-Area-Twin-Hull (SWATH) ship is a kind of high-performance vessel and has received much attention in many countries due to its excellent sea-keeping quality, less wave-making resistance, and wider deck area. However, the smaller water line will degrade the longitudinal restoring-moment while the Munk moment will increase at the speed of the square of the velocity of the ship, which may potentially lead to instability of the ship. Usually, in order to enhance the motion performance a pair of fin stabilizers are installed on the inside of the lower hulls. Therefore, the physical configuration and the control design for the fin stabilizers need further studies to meet some requirements such as high comfortabiliry and better adaptability to special operating platforms.At the beginning of this thesis, we present a brief review of the structural configuration and related research status of the SWATH. As a robust synthesis tool, the characteristics and designing process of the quantitative feedback theory (QFT) is formulated as the preliminaries to this thesis. The diagonal controllers and non-diagonal controllers based on QFT for a specific SWATH are proposed to deal with the high nonlinearity, coupling and parametric uncertainties. In view of the fact that the essence of QFT-based control is to transform the parametric uncertainties and external disturbances into the requirements of some performance indices, the controllers derived from QFT hold better robustness. The numerical simulation is to control the longitudinal motion of a SWATH under the following circumstances:the sea condition is at level five; the speed of the vehicle varies from17knots to30knots; actuators are concatenated with the vehicle. Simulation results demonstrate that the heaving and pitching motion has been inhibited to a smaller level after the SWATH is equipped with the QFT-based controllers. The simulations also show that the QFT-based controllers are not sensitive to the modeling uncertainties and external disturbances.