In this paper, model predictive controller was designed to the multi-constraints problem and nonlinear problem for dynamic positioning vessel. A nonlinear passive observer was designed to estimate the unmodeled environment forces to improve the accuracy of the controller. Augmented state-space model was established for the design of the MPC controller and the constraints of the maximum forces and the change-rate of the forces is taking into account to ensure the success of the thrusts allocation. The cost function takes into account the distance between the predicted output variables and the set-point. Numerical simulation results show the validity and efficiency of the proposed method.
With the exploration and exploitation of the hydrocarbons, dynamic marine vessels have been commercially available since the 1960's (Fossen, 1999). Dynamic positioning (DP) systems maintain marine vessels in a fixed position and heading angle in the horizontal plane or pre-determined track exclusively by means of active thruster(Sørensen, 2011).
Wave filtering and state estimation are important parts of DP system. The algorithm of Kalman filter was introduced in the 1960's (Kalman, 1960), but the kinematic equations of motion was linearized about predefined constant yaw angles, typically 36 operating points in steps of 10 degrees, to cover the whole heading envelope. In order to remove the assumption of linearization, Fossen, T. I (1998) proposed vectorial observer backstepping for DP estimation. However, this simplified model neglected the WF motion and bias states. Then, Aarset (1998) extended the case by including a dynamic model for wave filtering and bias states estimation. Both the parameters of Kalman filter and backstepping observer must be determined through experimental texting of the craft. The nonlinear passive observer was proposed simplify the tuning procedure. This observer can be used including wave filtering, bias state estimation, reconstruction of the low-frequency (LF) motion components from noise measurements of position, heading angle and noise-free estimate of the non-measured vessel(Fossen, 1999).