Extremum Seeking-Based Power Maximization in a Wave-Driven Glider

Wave energy is a promising renewable resource, yet traditional wave energy conversion (WEC) systems suffer from limitations due to their stationary deployment. In particular, stationary WECs require several months or even years for permitting and installation, and they cannot be relocated to suit evolving demands after their installation. While these limitations are not necessarily an issue for longterm deployments, they are problematic for applications such as disaster recovery or temporary power supplementation in island communities, which require rapid deployability. This work examines a mobile wave glider system that combines the principles of a rapidly deployable wave glider with an auxiliary power take-off (PTO) system that utilizes a fraction of the available wave power to charge an on-board battery through an active damper. The contribution of this work lies in a real-time power optimization scheme that combines a sea-state-driven, model-based lookup table (based on a customized model developed by the authors) with extremum seeking control (ESC) to learn a correction to the lookup table. This approach is based on the observation that the optimal corrections will exhibit limited, slow variation relative to the variations in the sea state itself. Simulations, driven by wave data from the island nation of Palau and a scaled model of the system, demonstrate the effectiveness of the proposed control strategy in achieving near-optimal energy harvesting.