Parameter Estimation and Indirect Adaptive Control of a Dynamically Positioned Surface Vessel

In this article dynamically positioned surface vessel model is considered. To achieve precise performance of the vessel with unknown parameters two control problem was solved. First one is online parametric identification. The estimation of unknown parameters of the surface vessel model is obtained by methods, which are gradient descent method, extended Kalman filter and dynamic regressor extension and mixing (DREM). Second problem is the design of the adaptive control based on the collected results from estimators. For this purposes inverse dynamics control is considered. The convergence of the system is shown in the modeling section. DREM estimation method showed best results.