盤尼西林發酵程序控制設計｜國立臺灣科技大學博碩士論文系統

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研究生：	田立德 Lester - Chan Lik Teck
論文名稱：	盤尼西林發酵程序控制設計 Control Design for Penicillin Fermentation
指導教授：	周宜雄 Yi-Shyong Chou
口試委員:	錢義隆 I-Lung Chien 王逢盛 Feng-Sheng Wang 錢玉樹 Yu-Shu Chien
學位類別：	碩士 Master
系所名稱：	工程學院 - 化學工程系 Department of Chemical Engineering
論文出版年：	2006
畢業學年度：	94
語文別：	英文
論文頁數：	103
中文關鍵詞：	差值進化演算法、模式預測控制、最適化、饋料式最適化
外文關鍵詞：	differential evolution, model predictive control, optimization, fed-batch optimization
相關次數：	點閱：258 下載：3
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　　盤尼西林是目前最廣泛應用的抗生素之ㄧ，盤尼西林通常以饋料批次生產。而饋料批次操作具有挑戰性因為它能提供進料基質不同的饋料方式，已達到生產的最適化需求，另外從控制的觀點，饋料批次的最適化進料方式是動態問題。
　　本研究的重點強調以模式為基礎的最適化控制設計，期望能補償系統因有參數變動，不確定等因素的影響原最適化的控制操作結果。本文主要利用差值進化法為最適化的主要工作，執行各項的最適化尋優工作，之後討論非線性輸出－輸入，適應控制和模式預測控制的設計與控制的成效。比較以上各種控制器在參數變動下的韌性控制結果。結果得到模式預測控制可以得到較滿意的結果。

Penicillin is one of the most widely used antibiotics and is used for many Gram-positive bacterial infections. The production of penicillin is usually operated in fed-batch mode. The optimization of a fed-batch process is challenging because it is a dynamical optimization process. In this work, the suitability of differential evolution as an optimization approach tested. Inspired by model predictive control, an algorithm was proposed to handle disturbance to a system. This incorporated differential evolution into the algorithm. Different cases were presented and the algorithm was able to perform satisfactorily.

Contents
Abstract	I
Acknowledgement	II
Contents	III
List of Figures	V
List of Table	VIII
Chapter 1	1
Introduction	1
1.1 Fed-Batch Fermentation	1
1.1 Literature Review	3
1.2 History of Penicillin	5
1.4 Motivation	8
1.5 Thesis Outline	8
Chapter 2	9
Problem Formulation	9
2.1 Penicillin production	9
2.2 Mechanistic Model for penicillin production	9
2.3 Problem definition	12
Optimization	15
3.1 Optimization Methods	15
3.1.1 Indirect methods	15
3.1.2 Deterministic direct methods	16
3.1.3 Stochastic direct methods	16
3.2 Differential evolution	19
3.2.1 Initialization	21
3.2.2 Mutation	22
3.2.3 Crossover	22
3.2.4 Selection	23
3.2.5 Schematic of DE	24
3.3 Optimization results and discussion	25
3.3.1 To find the final time tf	25
3.3.2 Application of DE in optimization of penicillin production	27
Chapter 4	38
4.1 Model Predictive Control (MPC)	38
4.1.1 Introduction to MPC	38
4.1.2 DE based MPC	41
4.2 Input-Output linearization method (IO)	43
4.2.1 Introduction to Input-Output	43
4.3 Results and Discussions	44
4.3.1 Determine the Control Criteria	44
4.3.1.1 Number of steps for MPC	44
4.3.1.2 Determine the state for best tracking	47
4.3.1.2.1 Biomass as output,	47
4.3.1.2.2 Substrate as output,	49
4.3.1.2.3 Volume as output,	51
4.3.2 Test Disturbance	53
Chapter 5	69
Conclusions	69
Future work	70
Nomenclature	71
References	73
Appendix A	76
Appendix B	80
Appendix C	89

                                

References
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全文公開日期 2011/07/28 (校內網路)
全文公開日期本全文未授權公開 (校外網路)
全文公開日期本全文未授權公開 (國家圖書館：臺灣博碩士論文系統)

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