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As a mature topic in chemical engineering, the book provides methods, problems and tools used in process control engineering. It discusses: process knowledge, sensor system technology, actuators, communication technology, and logistics, design and construction of control systems and their operation. The knowledge goes beyond the traditional process engineering field by applying the same principles, to biomedical processes, energy production and management of environmental issues. The book explains all the determinations in the "chemical systems" or "process systems", starting from the beginning of the processes, going through the intricate interdependency of the process stages, analyzing the hardware components of a control system and ending with the design of an appropriate control system for a process parameter or a whole process. The book is first addressed to the students and graduates of the departments of Chemical or Process Engineering. Second, to the chemical or process engineers in all industries or research and development centers, because they will notice the resemblance in approach from the system and control point of view, between different fields which might seem far from each other, but share the same control philosophy.
An application-oriented approach to process control. The reference text systematically explains process identification, control and optimization, the three key steps needed to solve a multivariable control problem. Theory is discussed as far as it is needed to understand and solve the defined problem, while numerous examples written in MATLAB illustrate the problem-solving approach.
Designed to be used as a text for advanced undergraduate and graduate courses in process control, as well as a reference for practising control engineers. It requires a strong background in mathematics and chemical engineering and aims to provide broad coverage of applied modern control theory.
A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable systems.
As a mature topic in chemical engineering, the book provides methods, problems and tools used in process control engineering. It discusses: process knowledge, sensor system technology, actuators, communication technology, and logistics, design and construction of control systems and their operation. The knowledge goes beyond the traditional process engineering field by applying the same principles, to biomedical processes, energy production and management of environmental issues. The book explains all the determinations in the "chemical systems" or "process systems", starting from the beginning of the processes, going through the intricate interdependency of the process stages, analyzing the hardware components of a control system and ending with the design of an appropriate control system for a process parameter or a whole process. The book is first addressed to the students and graduates of the departments of Chemical or Process Engineering. Second, to the chemical or process engineers in all industries or research and development centers, because they will notice the resemblance in approach from the system and control point of view, between different fields which might seem far from each other, but share the same control philosophy.
Filling a gap in the literature for a practical approach to the topic, this book is unique in including a whole section of case studies presenting a wide range of applications from polymerization reactors and bioreactors, to distillation column and complex fluid catalytic cracking units. A section of general tuning guidelines of MPC is also present.These thus aid readers in facilitating the implementation of MPC in process engineering and automation. At the same time many theoretical, computational and implementation aspects of model-based control are explained, with a look at both linear and nonlinear model predictive control. Each chapter presents details related to the modeling of the process as well as the implementation of different model-based control approaches, and there is also a discussion of both the dynamic behaviour and the economics of industrial processes and plants. The book is unique in the broad coverage of different model based control strategies and in the variety of applications presented. A special merit of the book is in the included library of dynamic models of several industrially relevant processes, which can be used by both the industrial and academic community to study and implement advanced control strategies.
Advanced Control Engineering provides a complete course in control engineering for undergraduates of all technical disciplines. Included are real-life case studies, numerous problems, and accompanying MatLab programs.
Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models to perform feasibility analyses of novel process designs, assess environmental impact, and detect potential hazards or accidents. To manage complex systems and enable process design, the behavior of systems is reduced to simple mathematical forms. This book provides a systematic approach to the mathematical development of process models and explains how to analyze those models. Additionally, there is a comprehensive bibliography for further reading, a question and answer section, and an accompanying Web site developed by the authors with additional data and exercises. - Introduces a structured modeling methodology emphasizing the importance of the modeling goal and including key steps such as model verification, calibration, and validation - Focuses on novel and advanced modeling techniques such as discrete, hybrid, hierarchical, and empirical modeling - Illustrates the notions, tools, and techniques of process modeling with examples and advances applications
Food materials are processed prior to their consumption using different processing technologies that improve their shelf life and maintain their physicochemical, biological, and sensory qualities. Introduction to Advanced Food Process Engineering provides a general reference on various aspects of processing, packaging, storage, and quality control and assessment systems, describing the basic principles and major applications of emerging food processing technologies. The book is divided into three sections, systematically examining processes from different areas of food process engineering. Section I covers a wide range of advanced food processing technologies including osmo-concentration of fruits and vegetables, membrane technology, nonthermal processing, emerging drying technologies, CA and MA storage of fruits and vegetables, nanotechnology in food processing, and computational fluid dynamics modeling in food processing. Section II describes food safety and various non-destructive quality assessment systems using machine vision systems, vibrational spectroscopy, biosensors, and chemosensors. Section III explores waste management, by-product utilization, and energy conservation in food processing industry. With an emphasis on novel food processes, each chapter contains case studies and examples to illustrate state-of-the-art applications of the technologies discussed.
This title will be the backbone of any plant, chemical, or process engineer's library. This is a broad area in which engineers need to be familiar with a wide array of techniques, technologies and equipment.