本文選題：批次過程 + 質(zhì)量控制��； 參考：《浙江大學(xué)》2015年碩士論文

【摘要】：基于過程模型的優(yōu)化方法是批次過程質(zhì)量控制與操作優(yōu)化的主流方法,然而其往往存在建模困難的問題；無模型優(yōu)化方法是近階段學(xué)者提出的優(yōu)化方法,然而其存在在線實(shí)驗(yàn)成本高的問題。本文結(jié)合一類批次過程快速、低成本、可重復(fù)性的特性,并借鑒基于過程模型的優(yōu)化方法與無模型優(yōu)化方法各自的優(yōu)點(diǎn),提出了一種迭代建模與信賴域優(yōu)化的方法,即局部建模、信賴域優(yōu)化、在線試驗(yàn)相結(jié)合的方法。其具有較高的優(yōu)化效率和較低的實(shí)驗(yàn)成本,一定程度上解決了建模過程中的模型失配問題,并且具有一定的收斂性。本文的主要研究內(nèi)容總結(jié)如下：迭代建模與信賴域優(yōu)化方法的關(guān)鍵之一是采用局部模型用于優(yōu)化,本文提出一種迭代建模的策略,確保局部模型的精度逐步得到提高；其主要包括模型結(jié)構(gòu)選擇、數(shù)據(jù)集更新和模型殘差校驗(yàn)。另一個(gè)關(guān)鍵點(diǎn)是信賴域優(yōu)化,本文利用信賴域優(yōu)化實(shí)現(xiàn)在優(yōu)化問題求解中對優(yōu)化步長的限制,確保迭代點(diǎn)的可信度和有效性。本文通過批次過程仿真算例驗(yàn)證了迭代建模與信賴域優(yōu)化方法的可行性和有效性。其中對兩類典型的優(yōu)化問題進(jìn)行了探討,分別為目標(biāo)函數(shù)未知的批次過程仿真優(yōu)化和約束函數(shù)未知的批次過程仿真優(yōu)化。通過對迭代過程的展示和分析,詳細(xì)地介紹了該方法的求解過程和結(jié)果,驗(yàn)證了方法在求解不同優(yōu)化命題中的可行性。本文還將此方法應(yīng)用于實(shí)際工業(yè)過程中一類典型的批次過程——注塑成型過程。同樣對兩種典型的優(yōu)化問題進(jìn)行了探討,分別為目標(biāo)函數(shù)未知和約束函數(shù)未知,即過程模型體現(xiàn)在目標(biāo)函數(shù)和約束函數(shù)中。實(shí)驗(yàn)結(jié)果證明了方法的可行性和有效性。本文還將該方法與傳統(tǒng)方法進(jìn)行了對比,實(shí)驗(yàn)結(jié)果有力地驗(yàn)證了該方法能更快更好地解決批次過程質(zhì)量控制與操作優(yōu)化問題。
[Abstract]:The optimization method based on process model is the mainstream method of batch process quality control and operation optimization.However, it has the problem of high cost of online experiment.In this paper, a method of iterative modeling and trust region optimization is proposed, which combines the characteristics of a class of batch processes such as fast, low cost and repeatable, and uses the advantages of process model-based optimization method and model-free optimization method for reference.Local modeling, trust region optimization and online test are combined.It has higher optimization efficiency and lower experimental cost, solves the model mismatch problem in the modeling process to a certain extent, and has certain convergence.The main research contents of this paper are summarized as follows: one of the keys of iterative modeling and trust region optimization is to use local model for optimization. In this paper, an iterative modeling strategy is proposed to ensure that the precision of local model is improved step by step;It mainly includes model structure selection, data set update and model residuals check.Another key point is trust region optimization. In this paper, we use trust region optimization to limit the step size of the optimization problem and ensure the reliability and validity of the iteration point.The feasibility and effectiveness of the iterative modeling and trust region optimization methods are verified by batch process simulation examples in this paper.Two kinds of typical optimization problems are discussed, one is batch process simulation optimization with unknown objective function and the other is batch process simulation optimization with unknown constraint function.Through the presentation and analysis of the iterative process, the solution process and results of the method are introduced in detail, and the feasibility of the method in solving different optimization propositions is verified.This method is also applied to a kind of typical batch process-injection molding process.At the same time, two typical optimization problems are discussed, which are unknown objective function and unknown constraint function, that is, the process model is embodied in the objective function and the constraint function.The experimental results show that the method is feasible and effective.The experimental results show that the method can solve the problem of batch process quality control and operation optimization more quickly and better.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TQ019;TP273

【參考文獻(xiàn)】

相關(guān)博士學(xué)位論文 前2條

1 孔祥松;快速、低成本間歇過程無模型優(yōu)化方法研究[D];浙江大學(xué);2011年

2 陳曦;基于質(zhì)量的注塑過程建模方法研究[D];浙江大學(xué);2001年

，

本文編號：1767119