Abstract: electrical mechanical equipment under complex operating conditions such as nonlinearity，time-varying dynamics，and strong coupling，an intelligent control model based on artificial intelligence algorithms is developed. The proposed model integrates a dual-layer intelligent control architecture combining deep feedforward and online optimization. Validated through simulation and hardware-in-the-loop experimental platforms，the model reduces the overshoot of system dynamic response by approximately 60% and shortens the settling time by about 40% compared with traditional PID and model predictive control，while exhibiting stronger robustness in the presence of unknown disturbances. The results demonstrate that the proposed intelligent control model significantly enhances the dynamic performance and adaptive capability of electrical mechanical equipment，providing an effective theoretical basis and technical approach for the construction of a new generation of intelligent power systems.