Multiple model adaptive wave filtering for dynamic positioning of marine vessels

This paper addresses a filtering problem that arises in the design of dynamic positioning systems for ships and offshore rigs subjected to the influence of sea waves. Its key contribution is twofold: i) it introduces an improved model for filter design, and ii) and it exploits the structure of a multiple model adaptive wave filter that relies on measurements of the vessel´s position and heading only. Namely, an improvement in the control plant model is proposed that better captures the physics of the problem at hand and a bank of Kalman filters is designed for a finite number of parameter values, each corresponding to a different peak frequency of the assumed wave spectrum model. Tools from multiple model adaptive estimation (MMAE) theory are exploited to blend the information provided by the different observers, yielding position and velocity estimates of the marine vessel. These estimates are then to be used in an appropriately designed feedback control law. Simulations illustrate the efficacy of the MMAE techniques proposed and the improvement in performance that is obtained when compared with other approaches.