Abstract
For an accurate automatic on-line measurement of ship's attitude the paper develops an intelligent sensing system which uses one servo-type accelerometer and two servo-type inclinometers appropriately located on the ship. By considering the dynamics of the servo-controlled rigid pendulums of the inclinometers, linear observation equations are derived on the rolling and pitching signals of the ship. Moreover, one accelerometer is utilized to extract the heaving signal. Through the introduction of linear dynamic models and the linear observation equations on the three signals, their on-line measurement is reduced to the state estimation of the linear dynamic systems. For unknown parameters in the dynamic models, candidates are introduced and a bank of Kalman filters are used to execute the on-line state estimation of the three signals. Furthermore, the following two methods for setting the candidates are examined to improve the accuracy of the measurement. First, all the candidates are set to be time-invariant and these values are chosen optimally from the viewpoint of the minimax criterion (method I). Second, new candidates, whose values are varied adaptively according to the changes of the unknown parameters with the time, are combined with the time-invariant candidates (method II). Both methods contribute largely to the high accuracy of the proposed on-line measurement system.
