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Author: Paul M.J. van den Hof
Publisher: Springer Science & Business Media
ISBN: 1441908951
Category : Technology & Engineering
Languages : en
Pages : 239
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Book Description
Model-Based Control will be a collection of state-of-the-art contributions in the field of modelling, identification, robust control and optimization of dynamical systems, with particular attention to the application domains of motion control systems (high-accuracy positioning systems) and large scale industrial process control systems.The book will be directed to academic and industrial people involved in research in systems and control, industrial process control and mechatronics.
Author: Paul M.J. van den Hof
Publisher: Springer Science & Business Media
ISBN: 1441908951
Category : Technology & Engineering
Languages : en
Pages : 239
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Book Description
Model-Based Control will be a collection of state-of-the-art contributions in the field of modelling, identification, robust control and optimization of dynamical systems, with particular attention to the application domains of motion control systems (high-accuracy positioning systems) and large scale industrial process control systems.The book will be directed to academic and industrial people involved in research in systems and control, industrial process control and mechatronics.
Author: Paul Serban Agachi
Publisher: John Wiley & Sons
ISBN: 3527609229
Category : Technology & Engineering
Languages : en
Pages : 290
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Book Description
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.
Author: Coleman Brosilow
Publisher: Prentice Hall Professional
ISBN: 9780130280787
Category : Computers
Languages : en
Pages : 712
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Book Description
Annotation In this book, two of the field's leading experts bring together powerful advances in model-based control for chemical process engineering. From start to finish, Coleman Brosilow and Babu Joseph introduce practical approaches designed to solve real-world problems -- not just theory. The book contains extensive examples and exercises, and an accompanying CD-ROM contains hands-on MATLAB files that supplement the examples and help readers solve the exercises -- a feature found in no other book on the topic.
Author: B. Wayne Bequette
Publisher: Prentice Hall Professional
ISBN: 9780133536409
Category : Computers
Languages : en
Pages : 804
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Book Description
Master process control hands on, through practical examples and MATLAB(R) simulations This is the first complete introduction to process control that fully integrates software tools--enabling professionals and students to master critical techniques hands on, through computer simulations based on the popular MATLAB environment. Process Control: Modeling, Design, and Simulation teaches the field's most important techniques, behaviors, and control problems through practical examples, supplemented by extensive exercises--with detailed derivations, relevant software files, and additional techniques available on a companion Web site. Coverage includes: Fundamentals of process control and instrumentation, including objectives, variables, and block diagrams Methodologies for developing dynamic models of chemical processes Dynamic behavior of linear systems: state space models, transfer function-based models, and more Feedback control; proportional, integral, and derivative (PID) controllers; and closed-loop stability analysis Frequency response analysis techniques for evaluating the robustness of control systems Improving control loop performance: internal model control (IMC), automatic tuning, gain scheduling, and enhancements to improve disturbance rejection Split-range, selective, and override strategies for switching among inputs or outputs Control loop interactions and multivariable controllers An introduction to model predictive control (MPC) Bequette walks step by step through the development of control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. The book also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve several key control problems, ranging from robustness analyses to biochemical reactors, biomedical problems to multivariable control.
Author: R. Berber
Publisher: Springer Science & Business Media
ISBN: 9780792335245
Category : Technology & Engineering
Languages : en
Pages : 846
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Book Description
Model based control has emerged as an important way to improve plant efficiency in the process industries, while meeting processing and operating policy constraints. The reader of Methods of Model Based Process Control will find state of the art reports on model based control technology presented by the world's leading scientists and experts from industry. All the important issues that a model based control system has to address are covered in depth, ranging from dynamic simulation and control-relevant identification to information integration. Specific emerging topics are also covered, such as robust control and nonlinear model predictive control. In addition to critical reviews of recent advances, the reader will find new ideas, industrial applications and views of future needs and challenges. Audience: A reference for graduate-level courses and a comprehensive guide for researchers and industrial control engineers in their exploration of the latest trends in the area.
Author: Arun Kumar Samantaray
Publisher: Springer Science & Business Media
ISBN: 1848001592
Category : Technology & Engineering
Languages : en
Pages : 489
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Book Description
This book provides control engineers and workers in industrial and academic research establishments interested in process engineering with a means to build up a practical and functional supervisory control environment and to use sophisticated models to get the best use out of their process data. Several applications to academic and small-scale-industrial processes are discussed and the development of a supervision platform for an industrial plant is presented.
Author: Panagiotis D. Christofides
Publisher: Springer Science & Business Media
ISBN: 9781402009365
Category : Science
Languages : en
Pages : 236
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Book Description
The interest in control of particulate processes has been triggered by the need to achieve tight distributed control of size distributions that greatly influence particulate product properties and quality. Drawing from recent advances in dynamics of infinite-dimensional systems and nonlinear control theory, control of particulate processes using population balances has evolved into a very active research area within the field of process control. This book - the first of its kind - presents general methods for the synthesis of nonlinear, robust and constrained feedback controllers for broad classes of particulate process models and illustrates their applications to industrially-important crystallization, aerosol and thermal spray processes. The controllers use a finite number of measurement sensors and control actuators to achieve stabilization of the closed-loop system, output tracking, attenuation of the effect of model uncertainty and handling of actuator saturation. Beginning with an introduction to control of particulate processes, the book discusses nonlinear order reduction and nonlinear, robust and constrained control of particulate spatially-homogeneous processes, and nonlinear control of spatially-homogeneous particulate processes. The synthesis of the controllers is performed by using geometric and Lyapunov-based control techniques. The book includes comparisons of the methods followed for controller synthesis with other approaches and discussions of practical implementation issues that can help researchers and engineers understand the development and application of the methods in greater depth. The methods are applied to continuous and batch crystallization processes, a titania aerosol reactor and a thermal spray process to regulate product size distribution. The resulting benefits in closed-loop performance, robustness and actuator saturation handling compared to other techniques for control of particulate processes are demonstrated through computer simulations. The book assumes a basic knowledge about population balances and nonlinear control. Researchers and graduate students in process control, particle technology and control systems theory, applied mathematicians and process control engineers will find this book a useful resource.
Author: Eduardo F. Camacho
Publisher: Springer Science & Business Media
ISBN: 1447130081
Category : Technology & Engineering
Languages : en
Pages : 250
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Book Description
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.
Author: Y. Zhu
Publisher: Elsevier
ISBN: 0080537111
Category : Technology & Engineering
Languages : en
Pages : 373
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Book Description
Systems and control theory has experienced significant development in the past few decades. New techniques have emerged which hold enormous potential for industrial applications, and which have therefore also attracted much interest from academic researchers. However, the impact of these developments on the process industries has been limited.The purpose of Multivariable System Identification for Process Control is to bridge the gap between theory and application, and to provide industrial solutions, based on sound scientific theory, to process identification problems. The book is organized in a reader-friendly way, starting with the simplest methods, and then gradually introducing more complex techniques. Thus, the reader is offered clear physical insight without recourse to large amounts of mathematics. Each method is covered in a single chapter or section, and experimental design is explained before any identification algorithms are discussed. The many simulation examples and industrial case studies demonstrate the power and efficiency of process identification, helping to make the theory more applicable. MatlabTM M-files, designed to help the reader to learn identification in a computing environment, are included.
Author: Jacques Richalet
Publisher: Springer Science & Business Media
ISBN: 1848824939
Category : Technology & Engineering
Languages : en
Pages : 236
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Book Description
first industrial application of MPC was in 1973. A key motivation was to provide better performance than could be obtained with the widely-used PID controller whilst making it easy to replace the PID controller unit or module with his new algorithm. It was the advent of digital control technology and the use of software control algorithms that made this replacement easier and more acceptable to process engineers. A decade of industrial practice with PFC was reported in the archival literature by Jacques Richalet et al. in 1978 in an important seminal Automatica paper. Around this time, Cutler and Ramaker published the dynamic matrix control algorithm that also used knowledge of future reference signals to determine a sequence of control signal adjustment. Thus, the theoretical and practical development of predictive control methods was underway and subsequent developments included those of generalized predictive control, and the whole armoury of MPC methods. Jacques Richalet’s approach to PFC was to seek an algorithm that was: • easy to understand; • easy to install; • easy to tune and optimise. He sought a new modular control algorithm that could be readily used by the control-technician engineer or the control-instrument engineer. It goes without saying that this objective also forms a good market strategy.
