Experimental Evaluation of Model-Based Predictive Control Applied to a Point Absorber

In this paper, we employ an experimentally designed Model Predictive Control (MPC) framework coupled with a Kalman filter to regulate a point absorber Wave Energy Converter (WEC). This methodology entails the utilization of a mathematical model representing the point absorber, enabling the controller to anticipate the energy converter's future behavior. Executing the MPC necessitates real-time data from sensors, which can be subject to white noise. Through the application of the Kalman filter, these inherent errors are effectively mitigated, enabling accurate estimation of adjusted state variables. This, in turn, leads to the generation of control signals and system outputs that correspond to position and velocity. The outcomes of the study highlight that this control strategy exerts a positive influence on power extraction, as it ensures alignment between velocity and excitation force, ultimately enhancing the efficiency of the process.