Current - Issue
Original Article
Reinforcement Learning-Based Adaptive Control Optimization Framework for Real-Time Control and Energy Maximization of Wave Energy Converters Considering Hydrodynamic and Environmental Uncertainties
Adel Elgammal1
1 Professor, Utilities and Sustainable Engineering, The University of Trinidad & Tobago, UTT.
Published Online: May-June 2026
Pages: 01-13
Cite this article
↗ https://www.doi.org/10.59256/ijire.20260703001
References
1. Bani Hani, Odai R., Zeiad Khafagy, Matthew Staber, Ashraf Gaffar, and Ossama Abdelkhalik. 2026. "Control of Wave Energy
Converters Using Reinforcement Learning" Journal of Marine Science and Engineering 14, no. 2: 211.
https://doi.org/10.3390/jmse14020211
2. J. Burhanudin, A. S. A. Hasim, A. M. Ishak, J. Burhanudin, and S. M. F. B. S. M. Dardin, ‘‘A review of power electronics for nearshore
wave energy converter applications,’’ IEEE Access, vol. 10, pp. 16670–16680, 2022
3. Trigueiro, J.; Botto, M.A.; Vieira, S.; Henriques, J. Control of a wave energy converter using reinforcement learning. In Proceedings
Converters Using Reinforcement Learning" Journal of Marine Science and Engineering 14, no. 2: 211.
https://doi.org/10.3390/jmse14020211
2. J. Burhanudin, A. S. A. Hasim, A. M. Ishak, J. Burhanudin, and S. M. F. B. S. M. Dardin, ‘‘A review of power electronics for nearshore
wave energy converter applications,’’ IEEE Access, vol. 10, pp. 16670–16680, 2022
3. Trigueiro, J.; Botto, M.A.; Vieira, S.; Henriques, J. Control of a wave energy converter using reinforcement learning. In Proceedings
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