A Real-Time PID Gain Method for Speed Regulation of Horizontal Centrifuges Via Improved Adaptive Genetic Algorithm
Yanfeng Xia a, Haotian Sun b, Yonghua Xu a, Junjie Sun , Boyang Sun a and Xintian Liu c
aEngineer, State Grid Shanghai Municipal Electric Power Company; Shanghai JiaYou City Construction Co., Ltd.; Shanghai Dongjie Construction (Group) Co., Ltd.
bGraduate Student, Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai, Shanghai 201620, China.
cProfessor, Department of Mechanical Engineering, Shanghai University of Engineering Science, Shanghai, Shanghai 201620, China.
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Abstract:
In centrifuge speed control, the gain coefficients of the PID controller (Proportional-Integral-Derivative controller) directly affect control performance and efficiency. Traditional parameter tuning relies on experience and trial-and-error, making it difficult to obtain optimal settings. To overcome this, an RT-PID-IAGA (Real-Time PID optimization based on Improved Adaptive Genetic Algorithm) is proposed. The method constructs a multi-objective fitness function considering speed error, overshoot, and settling time, and uses an adaptive genetic algorithm to optimize the PID coefficients in real time. A feedback-based control system is then established, enabling dynamic updating of parameters to maintain near-optimal performance. Comparative experiments with standard GA and conventional PID show that RT-PID-IAGA significantly improves control accuracy and response speed in centrifuge speed regulation.
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