Model predictive controller using Laguerre functions for dynamic positioning system

This paper develops an improved model predictive controller (MPC) for the dynamic positioning system of vessels by using the Laguerre functions. The set of Laguerre networks is introduced to describe the future control increment trajectory, which has fewer parameter to adjust. The improved model predictive controller have the advantages of the traditional model predictive control, which has the good control performance to deal with the multivariable and constraints. Besides, the number of parameters required in the optimization algorithm is fewer than the one required by the conventional MPC and the computation load online was also reduced. It is shown that the proposed MPC makes the closed-loop system asymptotically stable in the presence of input constraints. Simulation studies with comparisons on a supply vessel are carried out, and the results illustrate the effectiveness of the proposed control scheme.