Collective Blade Pitch Control Strategy for Floating Wind Turbines Based on Improved Tianji Horse Racing Optimization and Fuzzy Proportional Integral Double Derivative

This study aims to reduce the impact of wind and wave loads on the output power, rotor speed, and motion fluctuations of a floating wind turbine, while enhancing the anti-interference capability and addressing the strong coupling of the wind turbine system. Using a joint simulation based on OpenFAST and Simulink, this study focuses on offshore floating wind turbines consisting of the NREL 5MW turbine and a semi-submersible platform. A Fuzzy PIDD² (FPIDD²) collective pitch controller is designed, building on the OpenFAST baseline controller. The collective pitch controller helps mitigate wind and wave disturbances and improve the system resistance to external forces. Furthermore, to address the problem of rapid population diversity decline and the tendency to fall into local optima caused by the grouping competition mechanism in the Tianji Horse Racing Optimization (THRO) algorithm, an improved version, ITHRO, is proposed. This hybrid algorithm is applied to optimally tune the parameters of the FPIDD² controller, thereby enhancing its control performance. Finally, the control performance of the FPIDD² controller is compared with that of Fuzzy PID (FPID), PIDD², and the OpenFAST baseline controllers under varying wind and wave conditions. The results indicate that the FPIDD² controller significantly improves the stability of generator output power and rotor speed, while also reducing the motion fluctuations of the floating platform.