Application of Intelligent Control Strategy in Asynchronous Motor Speed Regulation System and Research on Energy Efficiency Improvement

Aiming at the shortcomings of traditional asynchronous motor speed control system in energy saving and control accuracy, this paper introduces intelligent control strategy, which aims to improve the response speed and energy efficiency of the speed control system through improved fuzzy logic control algorithm and adaptive PID controller (Proportion Integration Differentiation). Firstly, a speed control strategy based on fuzzy logic is proposed for the dynamic characteristics and load changes of the asynchronous motor speed control system. By constructing fuzzy rules between the motor speed and the control signal, the control accuracy of the system is optimized. Secondly, an adaptive PID controller is designed to adjust the PID parameters in real time with an adaptive algorithm to ensure that the system can maintain good control performance under load changes or external disturbances. By adjusting the proportional, integral, and differential gain parameters, the system can quickly restore to a stable state in an unstable environment. Finally, a large number of experiments are carried out to compare the performance of traditional PID control and the improved fuzzy adaptive PID control, and to evaluate its performance in energy efficiency and speed regulation accuracy. Under heavy load conditions (target speed 1800 rpm, load power 5-7.5 kW), the intelligent control strategy shows significant advantages in energy efficiency optimization and speed control. At 10 seconds, the cumulative energy consumption of traditional control is 95 kJ, while that of intelligent control is only 70 kJ. The combination of fuzzy logic and adaptive PID control in this paper optimizes the dynamic response performance and steady-state performance of the system, especially when the load changes greatly, the system shows better stability and energy saving effect.