Intelligent Temperature Control Method of Instrument Based on Fuzzy PID Control Technology

被引:0
|
作者
Li, Wenfang [1 ]
Wang, Yuqiao [1 ]
机构
[1] Huanghe Sci & Technol Univ, Fac Engn, Zhengzhou 450063, Peoples R China
关键词
Fuzzy PID control; instrumentation; intelligent temperature control; differential negative feedback; grey wolf optimization algorithm; WOLF OPTIMIZATION ALGORITHM; MAPS;
D O I
10.14569/IJACSA.2024.0150193
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The current instrumentation intelligent temperature control is generally realized based on PID control technology, whose efficiency and precision are low and cannot meet the actual production requirements. A fuzzy PID (FPID) control technique is suggested as a solution to this issue with the goal to increase the control precision by adjusting the PID parameters in real-time using a fuzzy algorithm. In addition, a multi -strategy -fused Improved Grey Wolf Optimization (MGWO) algorithm is used to obtain the optimal fuzzy rule parameters for the fuzzy controller to achieve the optimization of FPID. In addition to the aforementioned, the MGWO-FPID-based instrumentation intelligent temperature control model is created to enhance the instrumentation's ability to regulate temperature. The testing results demonstrated that the MGWO-FPID model outperformed the other two models with values for the objective function of 5 10-8, adaptation degree of 13.1, control regulation time of 2.08 s, F1 value of 96.14%, MAE value of 8.53, Recall value of 95.37%, and AUC value of 0.995. The above results prove that the MGWO-FPID-based instrumentation intelligent temperature control model proposed in the study has high accuracy and efficiency, which can effectively realize the instrumentation intelligent temperature control in industrial production, and then improve the accuracy and efficiency of instrumentation temperature control, ensure the safe production of industry, and promote the industrial development to a certain extent. This model can monitor and regulate the temperature in the industrial production process in real time, avoiding safety accidents caused by temperature anomalies, and ensuring the safety of industrial production. And the application of this model can improve the efficiency and product quality of industrial production, help reduce production costs and improve economic benefits. This can not only promote the development of related industries, but also drive the economic development of the entire society.
引用
收藏
页码:927 / 936
页数:10
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