This study proposes a Fuzzy Logic–based adaptive survivability control system for a heaving wave energy converter (WEC), aimed at ensuring safe, reliable, and self-sufficient operation across a wide range of sea states, including extreme conditions. Unlike conventional control strategies that primarily prioritize power maximization or structural considerations in isolation, the proposed AI-based control framework continuously evaluates environmental severity through a Survivability Risk Factor (SRF) and proactively adjusts the power take-off (PTO) behavior to mitigate operational risks. Under mild sea conditions, the controller promotes efficient power extraction, while during high-energy and extreme sea states, it actively limits heave motion, velocity, and PTO force to reduce mechanical stress and prevent excessive loading. The hybrid control framework integrates phase tuning/detuning and motion damping mechanisms, enabling adaptive regulation of PTO stiffness and damping in response to real-time sea state assessments derived from onboard sensor measurements. Comprehensive simulation results using measured wave elevation data demonstrate that the proposed system significantly enhances WEC survivability and operational robustness, achieving substantial reductions in motion amplitudes and PTO forces with only a modest loss in captured power during extreme events. The results highlight the effectiveness of the proposed adaptive survivability system in balancing energy extraction, long-term reliability, and system safety, offering a practical and scalable solution for intelligent energy system control in harsh marine environments.
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