## 2 The Development Stages of Grain-Drying Technology
### The Current State of Research on the Control Systems of Grain Dryers in China
#### 3.2.1 Intelligent Control Technology  
The rapid advancement of science and technology is driving innovation in the field of domestic grain-drying automatic control. The introduction of intelligent control methods has not only improved control efficiency but also brought higher precision and stability to the grain-drying process. Intelligent control combines computer technology and AI algorithms, enabling the automated control of complex systems through perception, learning, and adaptive capabilities. This type of control method is typically suitable for systems that need to handle characteristics such as nonlinearity, strong coupling, and fuzzy uncertainty, in order to enhance system performance and adaptability [77; 78].  
Table 5 comprehensively presents the research advancements in intelligent control technology, including its applications across various fields, historical origins, the impact brought by the introduction of neural networks, and future development directions integrating IoT and big data technologies.  
[PERSON] et al. [94], in order to address the issue of controlling systems for which precise mathematical models cannot be established, applied a two-dimensional structured fuzzy control algorithm to grain dryers. Experimental research indicated that the control effect of this system is satisfactory at temperatures ranging from 20 to 60 \({}^{\circ}\)C, achieving  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Time** & **Development Status** & **References** \\ \hline
1960s–1970s & Fuzzy control is a pioneer in the field of intelligent control, first proposed by the Japanese scholar [PERSON]. In 1965, [PERSON] proposed the theory of fuzzy sets, laying the foundation for fuzzy control. In the 1970s, fuzzy control began to be applied in industrial control systems. & [48; 79; 80] \\ \hline
1980s–1990s & The technology of expert systems has gradually come to prominence. Expert systems transform the knowledge of experts into a form that can be processed by computers, providing intelligent control systems with enhanced intelligent and adaptive capabilities. & [81; 82; 83] \\ \hline
1990s–2000s & Neural networks, as computational models that simulate the biological nervous system, have been introduced into the field of intelligent control. The powerful nonlinear mapping and learning capabilities of neural networks make intelligent control systems more adaptable and intelligent. & [84; 85; 86] \\ \hline
2000s–2010s & With the rapid development of deep learning technology, intelligent control has begun to expand in the direction of deep learning. The successful application of deep learning in fields such as image processing and speech recognition has brought more opportunities and challenges to intelligent control systems. & [87; 88; 89; 90] \\ \hline
2010s–hitherto & The swift advancement of IoT and big data technologies has opened up broader applications for intelligent control techniques. Intelligent control systems, by connecting with IoT devices, facilitate smarter data collection, analysis, and control. & [91; 92; 93] \\ \hline \hline \end{tabular}
\end{table}
Table 5: The development history timeline of intelligent control.  
fully automatic control of the grain-drying process. [PERSON] [61], addressing the challenges of nonlinearity, strong coupling, and hysteresis in the measurement parameters of the grain-drying process, developed an intelligent control system based on BPNN. According to the prediction of corn moisture content by BP, the system can adjust the grain discharge rate of the dryer, thereby precisely controlling the drying process. Finally, computer simulation technology was used to simulate the neural network control model, and the analysis results were compared with the experimental results for optimization. The results showed that the intelligent control system optimized by the BP algorithm, due to its excellent stability and strong anti-interference capability, can more efficiently manage and regulate the operation of the grain dryer.