Closes the gap between bioscience and mathematics-based process engineering
This book presents the most commonly employed approaches in the control of bioprocesses. It discusses the role that control theory plays in understanding the mechanisms of cellular and metabolic processes, and presents key results in various fields such as dynamic modeling, dynamic properties of bioprocess models, software sensors designed for the online estimation of parameters and state variables, and control and supervision of bioprocesses
Control in Bioengineering and Bioprocessing: Modeling, Estimation and the Use of Sensors is divided into three sections. Part I, Mathematical preliminaries and overview of the control and monitoring of bioprocess, provides a general overview of the control and monitoring of bioprocesses, and introduces the mathematical framework necessary for the analysis and characterization of bioprocess dynamics. Part II, Observability and control concepts, presents the observability concepts which form the basis of design online estimation algorithms (software sensor) for bioprocesses, and reviews controllability of these concepts, including automatic feedback control systems. Part III, Software sensors and observer-based control schemes for bioprocesses, features six application cases including dynamic behavior of 3-dimensional continuous bioreactors; observability analysis applied to 2D and 3D bioreactors with inhibitory and non-inhibitory models; and regulation of a continuously stirred bioreactor via modeling error compensation.
Control in Bioengineering and Bioprocessing is intended as a foundational text for graduate level students in bioengineering, as well as a reference text for researchers, engineers, and other practitioners interested in the field of estimation and control of bioprocesses.
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Pablo Antonio López Pérez, PhD, is Professor at Escuela Superior de Apan, Universidad Autónoma del Estado de Hidalgo, México. His research focuses on Modeling, simulation and nonlinear control of Reactors, Bioreactors and Photobioreactors.
Ricardo Aguilar López, PhD is Professor at the Department of Biotechnology and Bioengineering, Center for Research and Advanced Studies (Cinvestav), México. His research interests include modeling of biosystems and bioprocesses, dynamic analysis in bioreactors and design of nonlinear control schemes applied to biological systems, as well as the development of online bioprocess monitoring schemes.
Ricardo Femat, PhD was the General Director of the Institute for Scientific and Technological Research of San Luis Potosi (IPICYT), and a Professor in the Department of Applied Mathematics in México. His research interests include (i) analysis, characterization and control of systems with complex dynamics, (ii) the regulation of glucose level in diabetics and (iii) the control of processes with reaction and diffusion.
Closes the gap between bioscience and mathematics-based process engineering
This book presents the most commonly employed approaches in the control of bioprocesses. It discusses the role that control theory plays in understanding the mechanisms of cellular and metabolic processes, and presents key results in various fields such as dynamic modeling, dynamic properties of bioprocess models, software sensors designed for the online estimation of parameters and state variables, and control and supervision of bioprocesses.
Control in Bioprocessing: Modeling, Estimation and the Use of Soft Sensors is divided into three sections. Part I, Overview of the Control and Monitoring of Bioprocesses and Mathematical Preliminaries, provides a general overview of the control and monitoring of bioprocesses, and introduces the mathematical framework necessary for the analysis and characterization of bioprocess dynamics. Part II, Observability and control concepts, presents the observability concepts which form the basis of design online estimation algorithms (software sensor) for bioprocesses, and reviews controllability of these concepts, including automatic feedback control systems. Part III, Software sensors and observer-based control schemes for bioprocesses, features six application cases including dynamic behavior of 3-dimensional continuous bioreactors; observability analysis applied to 2D and 3D bioreactors with inhibitory and non-inhibitory models; and regulation of a continuously stirred bioreactor via modeling error compensation.
Control in Bioprocessing: Modeling, Estimation and the Use of Soft Sensors is intended as a foundational text for graduate level students in bioengineering, as well as a reference text for researchers, engineers, and other practitioners interested in the field of estimation and control of bioprocesses.
Closes the gap between bioscience and mathematics-based process engineering
This book presents the most commonly employed approaches in the control of bioprocesses. It discusses the role that control theory plays in understanding the mechanisms of cellular and metabolic processes, and presents key results in various fields such as dynamic modeling, dynamic properties of bioprocess models, software sensors designed for the online estimation of parameters and state variables, and control and supervision of bioprocesses.
Control in Bioprocessing: Modeling, Estimation and the Use of Soft Sensors is divided into three sections. Part I, Overview of the Control and Monitoring of Bioprocesses and Mathematical Preliminaries, provides a general overview of the control and monitoring of bioprocesses, and introduces the mathematical framework necessary for the analysis and characterization of bioprocess dynamics. Part II, Observability and control concepts, presents the observability concepts which form the basis of design online estimation algorithms (software sensor) for bioprocesses, and reviews controllability of these concepts, including automatic feedback control systems. Part III, Software sensors and observer-based control schemes for bioprocesses, features six application cases including dynamic behavior of 3-dimensional continuous bioreactors; observability analysis applied to 2D and 3D bioreactors with inhibitory and non-inhibitory models; and regulation of a continuously stirred bioreactor via modeling error compensation.
Control in Bioprocessing: Modeling, Estimation and the Use of Soft Sensors is intended as a foundational text for graduate level students in bioengineering, as well as a reference text for researchers, engineers, and other practitioners interested in the field of estimation and control of bioprocesses.
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