Yang Taoqing, Zheng Xia, Xiao Hongwei, Shan Chunhui, Yao Xuedong, Li Yican, Zhang Jikai
College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, China.
Key Laboratory of Northwest Agricultural Equipment, Ministry of Agriculture and Rural Affairs, Shihezi 832003, China.
Plants (Basel). 2023 Jun 9;12(12):2257. doi: 10.3390/plants12122257.
A drying temperature precision control system was studied to provide technical support for developing and further proving the superiority of the variable-temperature drying process. In this study, an improved neural network (INN) proportional-integral-derivative (PID) controller (INN-PID) was designed. The dynamic performance of the PID, neural network PID (NN-PID) and INN-PID controllers was simulated with unit step signals as an input in MATLAB software. A drying temperature precision control system was set up in an air impingement dryer, and the drying temperature control experiment was carried out to verify the performance of the three controllers. Linear variable-temperature (LVT) and constant-temperature drying experiments of cantaloupe slices were carried out based on the system. Moreover, the experimental results were evaluated comprehensively with the brightness ( value), colour difference (Δ), vitamin C content, chewiness, drying time and energy consumption (EC) as evaluation indexes. The simulation results show that the INN-PID controller outperforms the other two controllers in terms of control accuracy and regulation time. In the drying temperature control experiment at 50 °C-55 °C, the peak time of the INN-PID controller is 237.37 s, the regulation time is 134.91 s and the maximum overshoot is 4.74%. The INN-PID controller can quickly and effectively regulate the temperature of the inner chamber of the air impingement dryer. Compared with constant-temperature drying, LVT is a more effective drying mode as it ensures the quality of the material and reduces the drying time and EC. The drying temperature precision control system based on the INN-PID controller meets the temperature control requirements of the variable-temperature drying process. This system provides practical and effective technical support for the variable-temperature drying process and lays the foundation for further research. The LVT drying experiments of cantaloupe slices also show that variable-temperature drying is a better process than constant-temperature drying and is worthy of further study to be applied in production.
为了给变温干燥工艺的开发及进一步验证其优越性提供技术支持，对一种干燥温度精确控制系统进行了研究。在本研究中，设计了一种改进神经网络（INN）比例积分微分（PID）控制器（INN-PID）。在MATLAB软件中，以单位阶跃信号作为输入，对PID、神经网络PID（NN-PID）和INN-PID控制器的动态性能进行了仿真。在气流冲击干燥机中搭建了干燥温度精确控制系统，并进行了干燥温度控制实验，以验证这三种控制器的性能。基于该系统，对哈密瓜片进行了线性变温（LVT）和恒温干燥实验。此外，以亮度（值）、色差（Δ）、维生素C含量、咀嚼性、干燥时间和能耗（EC）作为评价指标，对实验结果进行了综合评价。仿真结果表明，INN-PID控制器在控制精度和调节时间方面优于其他两种控制器。在50℃-55℃的干燥温度控制实验中，INN-PID控制器的峰值时间为237.37 s，调节时间为134.91 s，最大超调量为4.74%。INN-PID控制器能够快速有效地调节气流冲击干燥机内腔的温度。与恒温干燥相比，LVT是一种更有效的干燥方式，因为它能保证物料质量，减少干燥时间和EC。基于INN-PID控制器的干燥温度精确控制系统满足变温干燥工艺的温度控制要求。该系统为变温干燥工艺提供了切实有效的技术支持，为进一步研究奠定了基础。哈密瓜片的LVT干燥实验还表明，变温干燥是一种比恒温干燥更好的工艺，值得进一步研究以应用于生产。
