Traditional control strategies that rely solely on the current state information of buoy, which exhibit low energy capture efficiency. Moreover, variations in sea conditions and modeling errors lead to mismatches in the buoy model parameters, further diminishing the performance of the controller. To address these issues, a non-causal optimization strategy is proposed based on adaptive control. This strategy utilizes real-time system states and future excitation force information to design feedback and feed forward components, employing backward recursive calculations of gain coefficients to derive the optimal control law. By using dynamic buoy information as input, the adaptive strategy is designed to match hydrodynamic parameters online, thereby reducing energy loss caused by model mismatches. Simulation results demonstrate that, compared to the sub-optimal causal control strategy, the non-causal control strategy achieves the highest energy capture, effectively constrains system displacement and electromagnetic force, and ensures safe system operation. Furthermore, in the presence of model mismatches, the proposed adaptive strategy effectively restores controller performance, enhancing wave energy capture rates under mismatched conditions.