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The book presents, in a systematic manner, the optimal controls under different mathematical models in fermentation processes. Variant mathematical models – i.e., those for multistage systems; switched autonomous systems; time-dependent and state-dependent switched systems; multistage time-delay systems and switched time-delay systems – for fed-batch fermentation processes are proposed and the theories and algorithms of their optimal control problems are studied and discussed. By putting forward novel methods and innovative tools, the book provides a state-of-the-art and comprehensive systematic treatment of optimal control problems arising in fermentation processes. It not only develops nonlinear dynamical system, optimal control theory and optimization algorithms, but can also help to increase productivity and provide valuable reference material on commercial fermentation processes.
Many, if not most, industrially important fermentation and bioreactor operations are carried out in fed-batch mode, producing a wide variety of products. In spite of this, there is no single book that deals with fed-batch operations. This is the first book that presents all the necessary background material regarding the 'what, why and how' of optimal and sub-optimal fed-batch operations. Numerous examples are provided to illustrate the application of optimal fed-batch cultures. This unique book, by world experts with decades of research and industrial experience, is a must for researchers and industrial practitioners of fed-batch processes (modeling, control and optimization) in biotechnology, fermentation, food, pharmaceuticals and waste treatment industries.
The purpose of this volume is to describe the components, assembly, and implementation of computer-based process control systems. Presented in two sections, it illustrates how such systems have been used to monitor and control industrial fermentation processes as a means to improve our understanding of product biosynthesis. This book covers the fields of indirect parameter estimation and fermentation-specific control algorithms. It also includes chapters which describe system architecture and process application, process control, on-line liquid sampling and computer system architecture. This is an ideal source for anyone involved with biotechnology, bioengineering, microbial technology, chemical engineering, and computer control.
Illustrating techniques in model development, signal processing, data reconciliation, process monitoring, quality assurance, intelligent real-time process supervision, and fault detection and diagnosis, Batch Fermentation offers valuable simulation and control strategies for batch fermentation applications in the food, pharmaceutical, and chemical industries. The book provides approaches for determining optimal reference trajectories and operating conditions; estimating final product quality; modifying, adjusting, and enhancing batch process operations; and designing integrated real-time intelligent knowledge-based systems for process monitoring and fault diagnosis.
Many fed-batch processes can be considered as a class of control affine nonlinear systems. In this paper, a new type of neural network for modelling fed-batch processes, called as Control Affine Feedforward Neural Network (CAFNN), is proposed. For constrained nonlinear optimal control of fed-batch processes, CAFNN offers an effective and simple optimal control strategy by sequential quadratic programming where the gradient information can be computed directly from CAFNN. Thus the nonlinear programming problem can then be solved more accurately and efficiently. The proposed modelling and optimal control scheme are illustrated on a nonlinear system and a simulated fed-batch ethanol fermentation process.