| 摘要: |
| 目的 为了提高无菌砖包设备预热系统温度控制精度，设计一种温度控制器。方法 基于模糊神经网络算法设计一种温度控制器。在预热系统硬件结构的基础上，建立被控对象数学模型。利用模糊控制的良好收敛性和对模糊量的运算优势，以及神经网络自学习、自适应的特性，将常规PID控制与模糊控制、神经网络结合起来，提出一种基于模糊神经网络的PID控制策略，以实现对PID参数的实时在线整定。结果 试验结果表明，与其他方法相比，所述控制方法能够将温度超调从2.6 ℃减小到0.9 ℃，稳态偏差从±1 ℃减小到±0.4 ℃。结论 该方法能够满足预热系统温度控制需求。 |
| 关键词: 无菌包装 预热温度 模糊神经网络 参数整定 |
| DOI：10.19554/j.cnki.1001-3563.2019.23.024 |
| 分类号:TB486 |
| 基金项目: |
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| Temperature Control Method of Aseptic Packaging Preheating System |
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GU Dong-hua, ZHOU Zhen
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Zhengzhou University of Light Industry, Zhengzhou 450000, China
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| Abstract: |
| The work aims to design a temperature controller, in order to improve the temperature control precision of the preheating system of aseptic brick bale equipment. A temperature controller was designed based on the fuzzy neural network algorithm. On the basis of hardware structure of the preheating system, the mathematical model of the controlled object was established. Taking advantage of the good convergence of fuzzy control and the operation advantage of fuzzy quantity, as well as the self-learning and self-adaptive characteristics of neural network, a PID control strategy based on fuzzy neural network was proposed by combining the conventional PID control with fuzzy control and neural network, so as to realize the real-time online tuning of PID parameters. Experimental results showed that, compared with other methods, the proposed control method could reduce the temperature overshoot from 2.6 ℃ to 0.9 ℃, and the steady-state deviation from ±1 ℃ to ±0.4 ℃. The proposed method can meet the requirement of preheating system temperature control. |
| Key words: aseptic packaging preheating temperature fuzzy neural network parameter setting |
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