Decentralized Model Predictive Control for Wave Energy Converter Arrays

Most of the research on wave energy conversion has been focused on the characterization of the dynamic behavior of arrays of uncontrolled wave energy converters (WECs) in specific configurations, in order to quantify changes in the wave fields and absorbed power without active control. To maximize wave energy conversion, however, it is necessary to apply active control techniques to the WECs that conform the array. In this paper, we propose the application of decentralized model predictive control (MPC) to the elements of an array by considering each individual WEC as a subsystem. Each decentralized MPC optimizes the absorbed power of its own WEC under the same input and state constraints that a centralized MPC otherwise would.