Dynamic Positioning Based on Nonlinear MPC

This paper is devoted to nonlinear model predictive control (MPC) application for dynamic positioning (DP) problem. The MPC approach has prominent features among other nonlinear control schemes. They include the explicit way for using nonlinear models and taking into account constraints imposed on controlled and manipulated variables while provide optimal performance with respect to a given cost functional. Dynamic positioning is a nonlinear control process with three-dimensional input and output, constraints and external disturbances that allows to state that MPC strategy is a quite suitable approach to be used here. In this paper MPC based control algorithm for DP problem is proposed. This algorithm includes two stages: the nonlinear stage, where nonlinear predictive model is used, and the linear stage, which is switch on in the vicinity of desired position. The algorithm provides offset-free performance. The effectiveness of the MPC approach is demonstrated by the simulation study examples.