Model predictive control for dynamic positioning system of ships with unknown time-varying disturbances and actuator constraint

Abstract

This paper proposes a disturbance compensating model predictive control (DCMPC) strategy for the dynamic positioning (DP) system of ships with unknown time-varying environmental disturbances and actuator saturation. The proposed strategy can make the position and heading of the dynamically positioned ship converge to the desired values without any priori knowledge about environmental disturbances. The extended state observer (ESO) is introduced to estimate the unknown environmental disturbances. Based on ESO, the DCMPC algorithm is proposed to deal with the unknown disturbances. Finally, the simulations are carried out on a dynamically positioned ship and simulation results show the effectiveness of the proposed control strategy.