【摘要】 传统控制策略仅含浮子当前状态信息，能量捕获效率低，且海况变化及建模误差使浮子模型参数不匹配，降低控制器性能，为此，提出基于自适应控制的非因果优化策略。利用系统实时状态及未来激振力信息设计反馈、前馈项，通过反向递归计算增益系数，获得最优控制律。以浮子动态信息为输入，设计自适应策略，在线匹配水动力参数，减少因模型失配造成的能量损缺。仿真结果表明，与因果次优控制策略相比，非因果控制策略捕获能量最高，系统位移与电磁力可得到有效约束，保证系统安全运行；模型失配时，所提自适应策略可有效恢复控制器性能，提高失配情况下的波能捕获率。更多还原

【Abstract】 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.更多还原