Application of Fuzzy and Clear Mathematical Models in Hybrid Control of the Process of Single-Stage Mincing of Frozen Meat

IF 0.1 Q4 ENGINEERING, MULTIDISCIPLINARY
Boris R. Kapovskiy, V. Pchelkina, A. Dydykin
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Abstract

Introduction. During one-stage mincing of frozen meat by milling, a change in the temperature of the boundary layer occurs resulting in plastic deformations of the raw meat and an increase in the size of the meat chips. The problem of regulating the operating parameters for the raw meat mincing process depending on its temperature can be solved through computer calculations of the temperature forecast of the meat boundary layer for several time intervals using fuzzy logic. The aim of the study was to develop an algorithm for hybrid control of single-stage mincing of frozen meat using fuzzy and clear mathematical control models. Aim of the Article. The article is aimed at developing a hybrid control algorithm for singlestage grinding of frozen meat using fuzzy and clear mathematical control models. Materials and Methods. The object of the study was the process of mincing frozen meat block (beef) with the use of a laboratory installation for a single-stage mincing with a capacity of 400 kg/hour. The E. Mamdani algorithm was used to develop a fuzzy mathematical control model. Mathematical modeling was carried out in the MATLAB, the Fuzzy Logic Toolbox package. Results. There was developed a model for fuzzy control of the operation of an intelligent control system (ICS) when forming a task for setting the operating parameters of the meat mincing process with the use of adaptive forecasting of meat temperature. For this model, the membership functions of the input and output variables and a rule base (knowledge base) were created. There was proposed a functional scheme of temperature control, which reflects the structure of a fuzzy control model for single-stage mincing. The advantages of this control include the fact that the system is given the function of continuous automated control of the temperature regime of mincing raw meat under the control of an industrial computer. Discussion and Conclusion. The results of temperature control can be used for further technological processing of meat. Using information about the temperature and chemical composition of raw meat, the ICS can realize the optimal mixing of minced meat ingredients. Artificial intelligence calculates all these characteristics of meat without the participation of a human operator. It makes it possible to fully automate the technological processing of meat in order to produce finished products of guaranteed high quality.
模糊和清晰数学模型在冷冻肉类单级粉碎过程混合控制中的应用
简介在用绞肉机对冻肉进行一段式绞肉过程中,边界层的温度会发生变化,导致生肉发生塑性变形和肉片尺寸增大。根据生肉绞碎过程的温度来调节操作参数的问题,可以通过使用模糊逻辑对几个时间间隔内肉边界层的温度预测进行计算机计算来解决。本研究的目的是利用模糊和清晰的数学控制模型,开发冻肉单级绞肉混合控制算法。文章的目的。文章旨在利用模糊和清晰的数学控制模型,开发冻肉单级绞肉的混合控制算法。材料和方法。研究对象是冻肉块(牛肉)的绞肉过程,使用实验室装置进行单级绞肉,绞肉能力为 400 公斤/小时。使用 E. Mamdani 算法建立了一个模糊数学控制模型。数学建模在 MATLAB 的模糊逻辑工具箱软件包中进行。结果在利用肉类温度的自适应预测形成肉类绞碎过程操作参数设置任务时,开发了智能控制系统(ICS)运行的模糊控制模型。为此模型创建了输入和输出变量的成员函数以及规则库(知识库)。提出了一种温度控制功能方案,它反映了单级绞肉机模糊控制模型的结构。这种控制方式的优点在于,该系统可在工业计算机的控制下,对绞肉机绞肉的温度进行连续自动控制。讨论和结论。温度控制的结果可用于肉类的进一步技术加工。利用有关生肉温度和化学成分的信息,ICS 可以实现碎肉配料的最佳混合。人工智能可以计算肉类的所有这些特性,无需人工操作。这样就可以实现肉类技术加工的完全自动化,从而生产出高质量的成品。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Engineering Technologies and Systems
Engineering Technologies and Systems ENGINEERING, MULTIDISCIPLINARY-
自引率
33.30%
发文量
29
审稿时长
12 weeks
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