电子科技2025，Vol.38Issue(8)：42-48,7.DOI:10.16180/j.cnki.issn1007-7820.2025.08.006
基于Smith预估器的制冷系统BP神经网络PID控制算法
Research on BP Neural Network PID Control Algorithm of Refrigeration System Based on Smith Predictor
摘要
Abstract
In view of the problems of large time delay,high coupling,nonlinearity and external interference in the actual operation of compression refrigeration system,a BP(Back Propagation)neural network PID(Proponential Integration Differentiation)control algorithm based on Smith predictor is proposed in this study.Smith predictor com-pensator is used to predict and compensate the actual output of the system,and its predictive compensation mecha-nism is used to eliminate the delay link of the system and alleviate the influence of time delay on the system.The self-learning ability of BP neural network is used to decouple the compressed refrigeration system into two independent loop systems,and PID parameters are adjusted to cope with the changes of the system and external interference.MATLAB simulation results show that the proposed control strategy has obvious advantages in improving the dynamic performance and anti-interference performance of refrigeration system.The adjustment time of superheat and evapora-tion temperature is reduced by 123 s and 204 s,and the overshoot is reduced by 5.27%and 10.22%.And it has good robustness under the condition of changing parameters,and also reduces the overshoot of control,which provides an effective control scheme for the stable operation of compression refrigeration system.关键词
压缩式制冷系统/模型辨识/Smith预估器/PID/多变量解耦/BP神经网络/MATLAB仿真/解耦控制Key words
compression refrigeration system/model identification/Smith predictor/PID/multivariate decou-pling/BP neural network/MATLAB simulation/decoupling control分类
信息技术与安全科学引用本文复制引用
杨远星,丁绪东,王俊超,吴东..基于Smith预估器的制冷系统BP神经网络PID控制算法[J].电子科技,2025,38(8):42-48,7.基金项目
山东省重大科技创新工程项目(2019JZZY020812) （2019JZZY020812）
山东省自然科学基金(ZR2020MF070) Major Science and Technology Innovation Project of Shandong(2019JZZY020812) （ZR2020MF070）
Natural Science Foundation of Shandong(ZR2020MF070) （ZR2020MF070）
