Self-Tuning Kalman Filter Design for Offshore Platform Coordinates Estimation

Abstract

Abstract In this paper, a self-tuning Kalman filter for offshore platform (OP) position supervision is designed. The complete OP motion is assumed to be composed of the low-frequency motion caused by the wind and undercurrent, and the high frequency motion caused by the sea-way. The state estimation problem for the model of the low-frequency OP motion, on which the in-service control is performed, is solved through two jointly operating Kalman filters: the first one is used for the estimation of the states of the low-frequency motion, and the second one is employed for the highfrequency one. The parameters of the first filter are automatically adapted to variations of the second filter.