Adaptive Online Monitoring of Translator Motion for Direct-Drive Wave Energy Converters under Marine Uncertainty

Accurate online monitoring of translator motion is essential for achieving reliable and precise control of direct-drive wave energy converter (DDWEC) systems. However, in complex marine environments, uncertainties caused by temperature changes, mechanical vibrations, biofouling, and debris entanglement inevitably degrade the accuracy of translator motion acquisition. To address these issues, an adaptive online monitoring method of translator motion for DDWEC systems is proposed in this paper. A wave-to-wire (W2W) state-space model is developed to capture the dynamic responses of the DDWEC system under realistic ocean wave excitation. Based on the W2W model, the proposed method introduces a robust adaptive spherical simplex filter (RASSF) to fuse position sensor measurements with state prediction results. The RASSF integrates an adaptive update mechanism for unknown sensor noise characteristics and a prediction uncertainty estimation revision strategy for W2W model parameter mismatches, ensuring robustness and computational efficiency of translator motion monitoring in DDWECs. The effectiveness and robustness of the proposed method are verified by offline validation and online simulation under various uncertainty scenarios.