输送带液压夹紧机构模糊PID与遗传算法协同精准控制OA

To meet the high-precision control requirements of the hydraulic system in underground conveyor belt clamping mechanisms,this paper proposes a fuzzy PID control strategy optimized by genetic algorithm(GA-FPID).The method aims to automatically tune optimal controller parameters through global optimization,overcoming the limitations of traditional PID that relies on trial-and-error for fixed parameter tuning.A hydraulic system model is constructed on the AMESim/Simulink platform,and three controllers—traditional PID,fuzzy PID,and GA-FPID—are designed for comparative analysis.Simulation results show that traditional PID achieves a settling time of 3 s,a maximum stroke error of 1.3 mm,a sinusoidal tracking error of 0.14 mm,and a lag time of 1 s.With dynamic parameter adjustment,fuzzy PID reduces the maximum error to 0.1 mm(a 92.3%improvement),the tracking error to 0.12 mm,and the lag time to 0.8 s.By optimizing the ITAE criterion,GA-FPID further improves performance:the settling time is reduced to 1 s(66.7%faster than fuzzy PID),the maximum error to 0.01 mm(90%improvement),the tracking error to 0.03 mm(75%lower than fuzzy PID),and the lag time to 0.2 s.By integrating the local adaptability of fuzzy control with the global optimization capability of genetic algorithms,GA-FPID simultaneously enhances response speed and steady-state accuracy,effectively suppressing safety risks such as hydraulic lock failure.This study provides a novel approach for precise control of underground intelligent equipment.