الفهرس 
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Abstract
Wave energy is considered a promising source of renewable energy with the capacity to lessen our dependence on traditional sources of fuels. However, conversion of wave energy is still a
fairly underdeveloped technology compared to more mature renewable technologies. Toincrease the productivity and lower the expenses the conversion process, this thesis concentrates on optimizing the energy extraction of heaving point absorber using soft computing techniques.This thesis proposes a real-time, adaptive, data-driven controller that maximizes energy harvesting while taking into account the physical limitations of the device in question. The proposed controller uses soft computing techniques to find the optimal control command based on instantaneous measurements of wave height, device displacement, velocity, and acceleration. Additionally, the controller considers the limitations of the device, such as the maximum force that can be supplied by the controller/Power Take Off (PTO) system.This research primarily introduces an innovative control strategy that displays considerable improvements in terms of both average extracted energy and EC performance criteria. In terms of average power extraction, our controller exhibited a noteworthy 63% enhancement over the state-of-the-art Model Predictive Control (MPC) controller in the literature. Furthermore, our proposed controller outperformed the industry-standard resistive controller, generating nearly four times more extracted power. When it comes to the EC performance criteria, our proposed controller displayed a significant improvement of 28% over the state-of-the-art controller.These considerable advancements underscore the effectiveness of our proposed control strategy in achieving energy maximization and efficiency objectives. Notably, our controller has been designed to operate online, adeptly handling the varying conditions of Wave Energy Converter(WEC) hydrodynamics due to the stochastic nature of sea waves. This adaptability lends it a substantial advantage over many conventional control methods, making it a promising candidate for future developments in the field.The limitations of this work are primarily related to the experimental setup used in the study,which was based on simulation models of the WEC system. As such, the validity of the resultsmay be affected by the assumptions and simplifications made in the models.Future work direction will focus on conducting experimental tests to validate the efficacy of the presented controller in real-world environment. Additionally, further research can be done to investigate the use of the proposed control techniques on other types of WECs.