Modelling and Optimization of Biotechnological Processes

Artificial Intelligence Approaches

Lei Zhi Chen, Sing Kiong Nguang, Xiao Dong Chen (Autoren)

Buch | Softcover

VIII, 123 Seiten

2010
Springer Berlin (Verlag)
978-3-642-06792-1 (ISBN)

Artikel merken

Mostindustrialbiotechnologicalprocessesareoperatedempirically.Oneofthe major di?culties of applying advanced control theories is the highly nonlinear nature of the processes. This book examines approaches based on arti?cial intelligencemethods,inparticular,geneticalgorithmsandneuralnetworks,for monitoring, modelling and optimization of fed-batch fermentation processes. The main aim of a process control is to maximize the ?nal product with minimum development and production costs. This book is interdisciplinary in nature, combining topics from biotechn- ogy, arti?cial intelligence, system identi?cation, process monitoring, process modelling and optimal control. Both simulation and experimental validation are performed in this study to demonstrate the suitability and feasibility of proposed methodologies. An online biomass sensor is constructed using a - current neural network for predicting the biomass concentration online with only three measurements (dissolved oxygen, volume and feed rate). Results show that the proposed sensor is comparable or even superior to other sensors proposed in the literature that use more than three measurements. Biote- nological processes are modelled by cascading two recurrent neural networks. It is found that neural models are able to describe the processes with high accuracy. Optimization of the ?nal product is achieved using modi?ed genetic algorithms to determine optimal feed rate pro?les. Experimental results of the corresponding production yields demonstrate that genetic algorithms are powerful tools for optimization of highly nonlinear systems. Moreover, a c- bination of recurrentneural networks and genetic algorithms provides a useful and cost-e?ective methodology for optimizing biotechnological processes.

Optimization of Fed-batch Culture of Hybridoma Cells using Genetic Algorithms.- On-line Identification and Optimization of Feed Rate Profiles for Fed-batch Culture of Hybridoma Cells.- On-line Softsensor Development for Biomass Measurements using Dynamic Neural Networks.- Optimization of Fed-batch Fermentation Processes using Genetic Algorithms based on Cascade Dynamic Neural Network Models.- Experimental Validation of Cascade Recurrent Neural Network Models.- Designing and Implementing Optimal Control of Fed-batch Fermentation Processes.- Conclusions.

Erscheint lt. Verlag	18.11.2010
Reihe/Serie	Studies in Computational Intelligence
Zusatzinfo	VIII, 123 p.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	211 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Themenwelt	Technik
Schlagworte	algorithm • algorithms • Artificial Intelligence • Biotechnology • Computer-Aided Design (CAD) • Control • Genetic algorithms • Intelligence • linear optimization • Modeling • Monitor • Networks • neural network • Neural networks • Optimization • Simulation
ISBN-10	3-642-06792-1 / 3642067921
ISBN-13	978-3-642-06792-1 / 9783642067921
Zustand	Neuware