State Estimation and Control for a Model Scale Passenger Ship with LQG Approach

Reducing the roll response of ships in between irregular waves is an important issue for operational requirements. This study presents a roll dynamics model for a passenger ship equipped with active fins. In the paper, a Kalman Filter (KF) is applied to accurately estimate all states from the measurement of total roll motion and roll velocity (based on fins and waves), even in the presence of measurement noise. Synchronously, a linear quadratic gaussian (LQG) controller actively drives the fins to minimize roll motion and velocity by taking the fin amplitude and rate saturations together. Two different sea state severity are modelled for the simulation purpose. Results demonstrate the success of the state estimation approach and the remarkable potential of the LQG strategy for roll reduction.