@inproceedings{2e879318dff342f2b6a2bdde71ef2017,
title = "Wave Excitation Force Prediction Methodology Based on Autoregressive Filters for Real Time Control",
abstract = "This paper presents a wave excitation force prediction methodology for a slider crank power take-off system (PTOS) based on autoregressive filters. This study shows the feasibility of half period and zero crossing prediction of the irregular ocean waves to keep phase lock condition between the generator and the wave excitation force. This is critically important for unidirectional continuous rotation of the generator to maximize energy extraction. Results from the prediction with different filter orders are analyzed to accommodate real time processing requirements. It has been shown that 10th order filter provides the good compromise of accuracy and timely processing.",
keywords = "autoregressive filter, prediction, slider-crank, wave energy converter, wave excitation force",
author = "{Hasan Khan}, {Md Rakib} and Karayaka, {H. Bora} and Yanjun Yan and Peter Tay and Yu, {Yi Hsiang}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; null ; Conference date: 03-04-2019 Through 06-04-2019",
year = "2019",
month = apr,
doi = "10.1109/GreenTech.2019.8767127",
language = "English",
series = "IEEE Green Technologies Conference",
publisher = "IEEE Computer Society",
booktitle = "2019 IEEE Green Technologies Conference, GreenTech 2019",
address = "United States",
}