电子科技2025，Vol.38Issue(7)：7-14,8.DOI:10.16180/j.cnki.issn1007-7820.2025.07.002
改进粒子群的压缩式制冷系统模糊PID解耦控制
Fuzzy PID Decoupling Control for Improved Particle Swarm Compression Refrigeration System
摘要
Abstract
In view of the complex conditions of high coupling,nonlinearity and external interference in the actu-al operation of compressive refrigeration system,this study proposes a fuzzy PID(Proportional Integration Differentia-tion)decoupling control strategy based on particle swarm optimization algorithm.The coupling effect between the e-vaporation temperature and superheat of the compression refrigeration system is eliminated by the series pre-feedback decoupler,and the dual-input and dual-output system is decoupled into two single-input single-output systems.The inertia weights are dynamically nonlinearly descended,and the control parameters of the fuzzy PID controller are optimized by the improved particle swarm algorithm,and the simulation experiments are carried out by MATLAB.The simulation results show that the overshoot of superheat and evaporation temperature is reduced by 30.6%and 42.7%,respectively,and the adjustment time is shortened by 225 s and 275 s after the fuzzy PID controller is opti-mized by the series decoupling controller and the improved PSO(Particle Swarm Optimization)algorithm.The above results show that the proposed method effectively suppresses the oscillation of the system,and the dynamic perform-ance of the system is significantly improved.关键词
压缩式制冷系统/模型辨识/模糊控制/PID/多变量解耦/改进粒子群优化算法/参数整定/惯性权重/MATLABKey words
compression refrigeration system/model identification/fuzzy control/PID/multivariate decoupling/improved particle swarm optimization algorithm/parameter setting/inertia weight/MATLAB分类
信息技术与安全科学引用本文复制引用
吴冬,丁绪东,孙昊,马浩翔,杨远星..改进粒子群的压缩式制冷系统模糊PID解耦控制[J].电子科技,2025,38(7):7-14,8.基金项目
山东省重大科技创新工程项目(2019JZZY020812)Major Science and Technology Innovation Project of Shandong(2019JZZY020812) （2019JZZY020812）
