To improve the control accuracy and interference resistance of actuator control systems in complex environments, a complete actuator control system solution has been designed. The system uses an STM32 controller as the core processing unit, integrating high-precision position sensors to build a multi-level control architecture. An improved model predictive control algorithm is proposed, which introduces extended state observers and multi-objective optimization strategies to estimate system states and external disturbances in real-time, achieving precise disturbance compensation. Experimental and test results show that, under electromagnetic interference and mechanical vibration conditions, the system’s stability and robustness are significantly enhanced, with error fluctuations of less than 0.03 mm, dynamic response time of 4.82 s, overshoot of 1.5%, steady-state error of 0.14 mm, and energy consumption reduced by 15%, all better than MPC, fuzzy control, and PID control methods under similar conditions. This research provides a comprehensive solution for hardware design and algorithm optimization in actuator control for industrial automation and precision manufacturing.
