Intelligent temperature and humidity control system for Daqu fermentation rooms using Smith predictor-based fuzzy PID

YANG Haili, School of Mechanical Engineering , Sichuan University of Science and Engineering , Yibin , Sichuan 644000 , China
LIAO Xilong, School of Mechanical Engineering , Sichuan University of Science and Engineering , Yibin , Sichuan 644000 , ChinaFollow
LIU Sai, Anhui Province Key Laboratory of Intelligent Solid-state Fermentation Technology , Bozhou , Anhui 236800 , China
HU Xinjun, School of Mechanical Engineering , Sichuan University of Science and Engineering , Yibin , Sichuan 644000 , China;Liquor Brewing Biological Technology and Application of Key Laboratory of Sichuan Province , Yibin , Sichuan 644000 , China
LI Lan, Anhui Province Key Laboratory of Intelligent Solid-state Fermentation Technology , Bozhou , Anhui 236800 , China
XIE Liangliang, School of Mechanical Engineering , Sichuan University of Science and Engineering , Yibin , Sichuan 644000 , China
CHEN Shan, Anhui Province Key Laboratory of Intelligent Solid-state Fermentation Technology , Bozhou , Anhui 236800 , China
FEI Lei, School of Mechanical Engineering , Sichuan University of Science and Engineering , Yibin , Sichuan 644000 , China

Corresponding Author(s)

廖锡龙（2000—），男，四川轻化工大学在读硕士研究生。E-mail：18980734913@163.com

Abstract

［Objective］ To address the strong delay and nonlinearity in the Daqu fermentation process.［Methods］ This study proposes a coordinated control strategy combining a Smith predictor and fuzzy proportional -integral -derivative (PID). By establishing a mathematical model of the fermentation process, the Smith predictor is used to compensate for the delay. Combined with fuzzy rules, the PID parameters are tuned online, achieving precise control of temperature and humidity.［Results］ Compared with traditional and fuzzy PID control, the temperature overshoot is reduced by 23.3% and 4.7%,respectively,while the adjustment time is shortened by 15.81% and 11.53%,respectively. For humidity, the overshoot is reduced by 31.4% and 5.7%, while the adjustment time is shortened by 34.57% and 23.66%, respectively.［Conclusion］ The proposed method ensures that the maximum deviation from the target temperature and humidity curves is less than 2 ℃ and 3% RH, respectively, with the error band stabilizing at ±1 ℃ and ±2% RH. The system demonstrates uniform control performance and strong robustness.

Publication Date

6-17-2026

First Page

Last Page

106

DOI

10.13652/j.spjx.1003.5788.2025.80584

Recommended Citation

Haili, YANG; Xilong, LIAO; Sai, LIU; Xinjun, HU; Lan, LI; Liangliang, XIE; Shan, CHEN; and Lei, FEI (2026) "Intelligent temperature and humidity control system for Daqu fermentation rooms using Smith predictor-based fuzzy PID," Food and Machinery: Vol. 42: Iss. 5, Article 12.
DOI: 10.13652/j.spjx.1003.5788.2025.80584
Available at: https://www.ifoodmm.cn/journal/vol42/iss5/12

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