Due to the present trend in the wind industry to operate in deep seas, floating offshore wind turbines (FOWTs) are an area of study that is expanding. FOWT platforms cause increased structural movement, which can reduce the turbine’s power production and increase structural stress. New FOWT control strategies are now required as a result. The gain-scheduled proportional-integral (GSPI) controller, one of the most used control strategies, modifies the pitch angle of the blades in the above-rated zone. However, this method necessitates considerable mathematical approximations to calculate the control advantages. This study offers an improved GSPI controller (OGSPI) that uses the grey wolf optimizer (GWO) optimization method to reduce platform motion while preserving rated power output. The GWO chooses the controller’s ideal settings. The optimization objective function incorporates decreasing the platform pitch movements, and the resulting value is used to update the solutions. The effectiveness of the GWO in locating the best solutions has been evaluated using new optimization methods. These algorithms include the COOT optimization algorithm, the sine cosine algorithm (SCA), the African vultures optimization algorithm (AVOA), the Harris hawks optimization (HHO), and the whale optimization algorithm (WOA). The final findings show that, compared to those caused by the conventional GSPI, the suggested OGSPI may successfully minimize platform motion by 50.48%.