Modeling And Advanced Control For Process Industries

Due to the complexity of the process operation and the requirements for high quality, low cost, safety and the protection of the environment, an increasing number of pulp and paper companies are in need of an advanced control technology to improve their process operation. This publication presents, for the first time, the theory of such an advanced control technology as well as various industrial applications associated especially with Paper Making. The reader will gain a better understanding of the most popular and advanced process control techniques and applications of these techniques in an important real-time process industry. The contents are based on the authors' own research on modeling and advanced control in this field.

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.

This title introduces the underlying theory and demonstrates practical applications in different process industries using hybrid modeling. It reviews hybrid modeling approach applicability in wide range of process industries, recommends how to increase hybrid model performance and throw Insights into cost efficient practices in modeling techniques Discusses advance process operation maximizing the benefits of available process knowledge and Includes real-life and practical case studies

Offering a different approach to other textbooks in the area, this book is a comprehensive introduction to the subject divided in three broad parts. The first part deals with building physical models, the second part with developing empirical models and the final part discusses developing process control solutions. Theory is discussed where needed to ensure students have a full understanding of key techniques that are used to solve a modeling problem. Hallmark Features: Includes worked out examples of processes where the theory learned early on in the text can be applied. Uses MATLAB simulation examples of all processes and modeling techniques- further information on MATLAB can be obtained from www.mathworks.com Includes supplementary website to include further references, worked examples and figures from the book This book is structured and aimed at upper level undergraduate students within chemical engineering and other engineering disciplines looking for a comprehensive introduction to the subject. It is also of use to practitioners of process control where the integrated approach of physical and empirical modeling is particularly valuable.

Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.

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.

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. This volume by Professor Eduardo F. Camacho and his colleagues Manuel Berenguel and Francisco R. Rubio is an exemplar of what an Advances in Industrial Control monograph should be. In it the control of a thermal solar facility is used to study the performance obtainable from an interesting range of control algorithms. These methods range from the conventional PID controller, through to model-based predictive and robust optimal control methods and finishing with two fuzzy logic based control techniques. The scientific methodology applied is modelling, simulation and plant implementation. In the last chapter, a rigorous approach for a comparative study is described involving a careful selection of performance metrics. The text is rich in relevant up-to-date source material, and contains many thought-provoking comments. The presentation is well-balanced, impartial and very readable.

This compact and original reference and textbook presents the most important classical and modern essentials of control engineering in a single volume. It constitutes a harmonic mixture of control theory and applications, which makes the book especially useful for students, practicing engineers and researchers interested in modeling and control of processes. Well written and easily understandable, it includes a range of methods for the analysis and design of control systems.