Model Predictive Control Strategy Based on Linear Regression for Wave Energy Converter
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1068-3_33
Reference10 articles.
1. Nasrollahi, S., Kazemi, A., Jahangir, M.-H., Aryaee, S.: Selecting suitable wave energy technology for sustainable development, an MCDM approach. Renew. Energy 202, 756–772 (2023). https://doi.org/10.1016/j.renene.2022.11.005
2. Pelc, R., Fujita, R.M.: Renewable energy from the ocean. Mar. Policy 26, 471–479 (2002). https://doi.org/10.1016/S0308-597X(02)00045-3
3. Temiz, I., Leijon, J., Ekergård, B., Boström, C.: Economic aspects of latching control for a wave energy converter with a direct drive linear generator power take-off. Renew. Energy 128, 57–67 (2018). https://doi.org/10.1016/j.renene.2018.05.041
4. Huang, X., Sun, K., Xiao, X.: A neural network-based power control method for direct-drive wave energy converters in irregular waves. IEEE Trans. Sustain. Energy 11, 2962–2971 (2020). https://doi.org/10.1109/TSTE.2020.2984328
5. Li, J., Wang, F., Ke, D., Li, Z., He, L.: Weighting factors design of model predictive control for permanent magnet synchronous machine using particle swarm optimization. Trans. China Electrotech. Soc. 36, 50–59+76 (2021). https://doi.org/10.19595/j.cnki.1000-6753.tces.200752. (in Chinese)
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