加热过程模型。综述

N. Ismail, M. Rahiman, M. Taib
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引用次数: 1

摘要

本文综述了食品、制造业和农业加热过程模型的研究进展。本文以表格的形式总结了不同的加热过程建模技术及其在各种应用中的发展。发展加热过程的技术有很多,其中一些是数值法、第一性原理法、系统辨识法以及第一性原理与系统辨识法的结合。在回顾中,发现加热是一个线性过程,并对加热过程的线性模型进行了更多的回顾。它们是有限脉冲响应(FIR)模型、外生输入自回归(ARX)模型、自回归移动平均(ARMA)模型、外生输入自回归移动平均(ARMAX)模型、输出误差(OE)模型和Box-Jenkins (BJ)模型。其中,综述强调了ARX模型结构最简单,易于找到解析解,性能优异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Models for heating process — A review
This paper presents a review on models for heating process in food, manufacturing and agricultural industries. The review come out with the table to summary on different modeling technique and their developed models for heating process in various applications. There are many techniques to develop the heating process and some of them are numeric, first principle, system identification and a combination of first principle and system identification. During the review, it was found that heating is a linear process and more review for linear model on heating process are done. They are Finite Impulse Response (FIR), Auto-Regressive with Exogenous Input (ARX) model, Auto-Regressive Moving Average (ARMA) model, Auto-Regressive Moving Average with Exogenous Input (ARMAX) model, Output-Error (OE) model and Box-Jenkins (BJ) model. Among all, the review has highlighted that ARX model is the simplest structure, easy to find analytical solutions and provide excellent performance.
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