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The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC‐Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph‐theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.
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A Robust Optimal Control for Docking and Charging Unmanned Underwater Vehicles Powered by Wave Energy
This paper introduces a simulation framework and a corresponding Robust Optimal Control (ROC) for docking Unmanned Underwater Vehicles (UUVs) that leverages Marine Renewable Energy (MRE) for improved autonomy in docking and charging operations. The proposed simulation framework integrates the dynamics of the Wave Energy Converter (WEC), docking station, and UUV within a unified system. Utilizing the WEC-Sim for the hydrodynamic modeling and MoorDyn for mooring dynamics, and in-house UUV dynamics in Simulink, the simulation effectively accounts for complex interactions under dynamic ocean conditions. The ROC docking controller, consisting of a Linear Quadratic Regulator (LQR) and a Sliding Mode Control (SMC), is designed to enhance robustness against environmental disturbances and system uncertainties. This controller utilizes input-output linearization to transform the nonlinear dynamics into a manageable linear form, optimizing docking performance while compensating for disturbances and uncertainties. The combined simulation and control approach is validated under various ocean conditions, demonstrating effective docking precision and energy efficiency. This work lays a foundational platform for future advancements in autonomous marine operations for UUV docking systems integrated with WEC. In addition, this work also demonstrates the feasibility of using MRE to significantly extend the operational duration of UUVs; such a platform will be leveraged for further development of structural health monitoring and fault diagnosis techniques for offshore structures such as WECs and Floating Offshore Wind Turbines.
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- Award ID(s):
- 2138522
- PAR ID:
- 10584060
- Publisher / Repository:
- University Marine Energy Research Community
- Date Published:
- Format(s):
- Medium: X
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.5281/zenodo.15185426
