We develop wave energy converter control systems to exploit large-motion, nonlinear behaviors. Our faculty and students adapt various strategies, including online optimization, machine learning, and optimal control.
Nonlinear hydrodynamic models from non-cylindrical point absorber buoy designs harmonize buoy motion with generator forces. Future predictions of wave forces are estimated from upwind wave measurements using machine learning to improve energy extraction further. Multiphysics, model-based control is of particular interest addressing the coupled mechanical and electrical aspects of marine energy extraction.
Validated models, simulation, and testing are critical components of our work. Our students develop these skills during their research projects and through internships at Sandia National Laboratories and the U.S. National Renewable Energy Laboratory. If you are interested in learning more we encourage you to send us a message.
Model Predictive Control Schedule.
Sliding Mode Controller Energy Absorbed vs Other Control Strategies.
Nonlinear Model Predictive Control poster presentation at the Graduate Research Colloquium.
Block diagram of the decomposed excitation force and Proportional Derivative Complex Conjugate Control
Frictionless WEC using air-bearings for control algorithms testing.
Madelyn Veurink presenting at IEEE OCEANS 2022.