Active disturbance rejection controller design for dynamically positioned vessels based on adaptive hybrid biogeography-based optimization and differential evolution

Vessels with a dynamic positioning system (DPS) are widely applied in ocean resource exploration. Because of the inaccuracy and coupling of the vessel dynamic model, it is important to design a controller that performs well in an oceanic environment. The active disturbance rejection controller (ADRC) is introduced in this study to control the vessel movement and positioning in the DPS. The merit of the ADRC is that it does not need an accurate plant and disturbance model. In the proposed method, an adaptive hybrid biogeography-based optimization (BBO) and differential evolution (DE) are developed. The orthogonal learning (OL) mechanism is employed to achieve adaptive switching to different searching mechanisms between BBO and DE. The proposed adaptive hybrid BBO-DE (AHBBODE) algorithm is then used to optimize the parameters of ADRC; these parameters are not easy to determine by using the trial and error method. Finally, the proposed method is compared with the BBO- and DE-based methods. The results show that better performance is obtained by the proposed method.