一种基于无模型自适应控制和神经网络的糖沸的新型控制方法
Guancheng Lu1, Yanmei Meng1, Juan Huang2
1School of Mechanical Engineering, Guangxi University, Nanning, China.
Journal of food science
|November 8, 2025
概括
使用神经网络的新适应性控制方法通过增强晶体均性和糖吸收来改善糖的沸. 与传统方法相比,这种先进的技术提供了更高的表面纯度.
科学领域:
- 食品科学与技术 食品科学与技术
- 工艺控制工程 工艺控制工程
- 人工智能在制造业中的应用
背景情况:
- 糖沸涉及复杂的非线性动态,使精确的控制具有挑战性.
- 现有的手动控制和PID控制等方法在优化晶体均性和表面纯度方面存在局限性.
- 有效的控制对于最大限度地提高糖产量和产品质量至关重要.
研究的目的:
- 开发一种新的适应性控制方法来控制糖沸.
- 整合无模型的自适应控制和神经网络,以加强流程管理.
- 在糖沸过程中改善糖的吸收和晶体均性.
主要方法:
- 提出了一个与神经网络集成的无模型自适应控制策略.
- 神经网络被用来计算基于石和糖水平偏差的门开放系数.
- 该方法采用了自适应控制原则,以动态管理糖沸过程.
主要成果:
- 拟议的自适应控制方法实现了22.52%的表面纯度.
- 这超过了手动方法 (21.53%) 和基于PID的控制方法 (21.31%).
- 这种新方法证明了较好的晶体均性,颜色值和明显的纯度差异.
结论:
- 集成的无模型自适应控制和神经网络方法为糖沸提供有效的自适应控制.
- 这种先进的技术显著提高了关键的糖沸参数,如表面纯度和晶体均性.
- 建议采用这种方法用于自动化糖沸系统,以优化产品质量.
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