Abstract: A smart composite control strategy combining fuzzy control and PID control is proposed and applied to the control of an AC servo system. Fuzzy control is used to adaptively adjust the parameters of the PID controller online, thereby achieving relatively ideal static and dynamic performance indicators. Experimental results show that the AC servo system based on fuzzy PID control has the characteristics of fast response speed, high steady-state accuracy, and strong robustness. Keywords: Fuzzy control; PID control; AC servo system AC motor servo drive systems have gradually become the foundation of modern industries due to their simple structure and ease of maintenance. AC servo systems are increasingly widely used in joint drives for robots and manipulators, as well as in precision CNC machine tools. AC servo systems consist of AC motors. The digital model of an AC motor is not a simple linear model but exhibits nonlinearity, time-varying characteristics, and coupling, making it difficult to effectively control using traditional object-model-based control methods. For the performance of AC servo systems, on the one hand, good tracking performance is required, meaning the system must respond quickly to input signals, have small tracking errors, short transition times, and little or no overshoot, with few oscillations. On the other hand, high steady-state accuracy is required, meaning the system's steady-state error is small and positioning accuracy is high. In AC servo control, conventional control methods are generally based on PID control. However, simple PID control has drawbacks such as large overshoot, long settling time, and low control efficiency, and its parameter selection is relatively difficult. With the development of computer technology, artificial intelligence methods are used to store the operator's adjustment experience as knowledge in the computer. Based on the actual situation on site, the computer can automatically adjust the PID parameters, thus giving rise to intelligent PID controllers. Fuzzy control has a weak dependence on mathematical models and does not require the establishment of precise mathematical models of the process. This paper addresses the respective characteristics of fuzzy control and PID control, applying fuzzy inference to achieve online self-tuning of PID parameters. A fuzzy adaptive PID controller is designed for real-time position control of an AC servo system, resulting in relatively ideal static and dynamic performance indicators. For details, please click: AC Servo System Based on Fuzzy PID Control