Optimization study of motor speed control system based on PID control

With the rapid development of industrial automation, the performance requirements of motor speed control system become more and more demanding. In this paper, a fuzzy immune PID algorithm is proposed for the shortcomings of traditional PID controllers in motor speed regulation in order to improve the system's anti-interference ability and regulation accuracy. In this paper, the hardware architecture of the motor intelligent speed regulation system is first designed, including core components such as STM32 microcontroller, DC motor and IRS21867 driver chip. Through an in-depth analysis of the immune feedback algorithm and PID control principle, a fuzzy immune PID controller is constructed, and the PID parameters are dynamically adjusted using fuzzy inference rules. The experimental results show that the proposed fuzzy immune PID algorithm exhibits faster response speed and smaller error in motor speed regulation, with significant performance improvement compared with the conventional PID algorithm. The effectiveness and feasibility of the algorithm in the motor speed regulation system are verified through the simulation of interference experiments and speed error tests, showing good application prospects.