Batch Fermentation: Modeling: Monitoring, and Control

Author:   Ali Cinar (Illinois Institute of Technology, Chicago, USA) ,  Satish J. Parulekar ,  Cenk Undey (Illinois Institute of Technology, Chicago, Illinois, USA) ,  Gulnur Birol (Northwestern University, Evanston, Illinois USA)
Publisher:   Taylor & Francis Inc
Volume:   93
ISBN:  

9780824740344


Pages:   646
Publication Date:   01 April 2003
Format:   Hardback
Availability:   In Print   Availability explained
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Batch Fermentation: Modeling: Monitoring, and Control


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Overview

This reference offers simulation and control strategies for batch fermentation applications in the food, pharmaceutical and chemical industries. It provides approaches for determining optimal reference trajectories and operating conditions.

Full Product Details

Author:   Ali Cinar (Illinois Institute of Technology, Chicago, USA) ,  Satish J. Parulekar ,  Cenk Undey (Illinois Institute of Technology, Chicago, Illinois, USA) ,  Gulnur Birol (Northwestern University, Evanston, Illinois USA)
Publisher:   Taylor & Francis Inc
Imprint:   CRC Press Inc
Volume:   93
Dimensions:   Width: 15.60cm , Height: 3.40cm , Length: 23.40cm
Weight:   0.972kg
ISBN:  

9780824740344


ISBN 10:   0824740343
Pages:   646
Publication Date:   01 April 2003
Audience:   Professional and scholarly ,  Professional and scholarly ,  Professional & Vocational ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Introduction: characteristics of batch processes; focus areas of the book; penicillin fermentation; outline of the book. Kinetics and process models: introduction and background; mathematical representation of bioreactor operation; bioreactoroperation modes; conservation equations for a single bioreactor; unstructured kinetic models; structured kinetic models; case studies. Experimental data collection: sensors; computer-based data acquisition; statistical design of experiments; datapretreatment - outliers and data reconciliation; data pretreatment - signal noise reduction; theoretical confirmation/stoichiometry and energetics of growth. Linear data-based model development: principal components analysis; multivariable regressiontechniques; input-output modelling of dynamic processes; functional data analysis; multivariate statistical paradigms for batch process Modelling; artificial neural networks; extensions of linear modelling techniques to nonlinear model development. Systemscience methods nonlinear model development: deterministic systems and chaos; nonlinear time series analysis; model development; software resources. Statistical process monitoring: SPM based on univariate techniques; SPM of continuous processes withmultivariate statistical techniques; data length equalization and determination of phase landmarks in batch fermentation; multivariable batch processes; on-line monitoring of batch/fed-batch fermentation processes; monitoring of successive batch runs.Process control: introduction; open-loop (optimal) control; forced periodic operations; feedback control; optimal linear-quadratic feedback control; model predictive control. Fault diagnosis: contribution plots; statistical techniques for fault diagnosis;model-based fault diagnosis techniques; model-free fault diagnosis techniques. Related developments: role of metabolic engineering in process improvement; contributions of MFA and MCA to modelling; dynamic optimization of batch process operations;integrated supervisory KBS for on-line process supervision.

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Ali Cinar (Illinois Institute of Technology, Chicago, USA) (Author) , Satish J. Parulekar (Illinois Inst. of Technology) (Author) , Cenk Undey (Illinois Institute of Technology, Chicago, Illinois, USA) (Author) , Gulnur Birol (Northwestern University, Evanston, Illinois USA) (Author)

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