Industrial Process Identification and Control Design

Industrial Process Identification and Control Design

Author: Tao Liu

Publisher: Springer Science & Business Media

Published: 2011-11-16

Total Pages: 487

ISBN-13: 0857299778

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Industrial Process Identification and Control Design is devoted to advanced identification and control methods for the operation of continuous-time processes both with and without time delay, in industrial and chemical engineering practice. The simple and practical step- or relay-feedback test is employed when applying the proposed identification techniques, which are classified in terms of common industrial process type: open-loop stable; integrating; and unstable, respectively. Correspondingly, control system design and tuning models that follow are presented for single-input-single-output processes. Furthermore, new two-degree-of-freedom control strategies and cascade control system design methods are explored with reference to independently-improving, set-point tracking and load disturbance rejection. Decoupling, multi-loop, and decentralized control techniques for the operation of multiple-input-multiple-output processes are also detailed. Perfect tracking of a desire output trajectory is realized using iterative learning control in uncertain industrial batch processes. All the proposed methods are presented in an easy-to-follow style, illustrated by examples and practical applications. This book will be valuable for researchers in system identification and control theory, and will also be of interest to graduate control students from process, chemical, and electrical engineering backgrounds and to practising control engineers in the process industry.


Practical Grey-box Process Identification

Practical Grey-box Process Identification

Author: Torsten P. Bohlin

Publisher: Springer Science & Business Media

Published: 2006-09-07

Total Pages: 363

ISBN-13: 1846284031

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This book reviews the theoretical fundamentals of grey-box identification and puts the spotlight on MoCaVa, a MATLAB-compatible software tool, for facilitating the procedure of effective grey-box identification. It demonstrates the application of MoCaVa using two case studies drawn from the paper and steel industries. In addition, the book answers common questions which will help in building accurate models for systems with unknown inputs.


Multivariable System Identification For Process Control

Multivariable System Identification For Process Control

Author: Y. Zhu

Publisher: Elsevier

Published: 2001-10-08

Total Pages: 373

ISBN-13: 0080537111

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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.


From Plant Data to Process Control

From Plant Data to Process Control

Author: Liuping Wang

Publisher: CRC Press

Published: 2000-08-31

Total Pages: 250

ISBN-13: 9780748407019

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Process engineering spans industrial applications in the manufacturing sector from petrochemical to polymer to mineral production. From Plant Data to Process Control covers the most up-to-date techniques and algorithms in the area of process identification (PID) and process control, two key components of process engineering, essential for optimizing production systems. It examines both the theoretical advances in process design and control theory, and a wide variety of implementations. A wide variety of approaches are presented for building models of dynamical systems based on observed data (process identification) and for making the output of a system behave in a desired fashion by properly selecting the process input (process control).


Industrial Process Identification

Industrial Process Identification

Author: Ai Hui Tan

Publisher: Springer

Published: 2019-01-01

Total Pages: 232

ISBN-13: 3030036618

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Industrial Process Identification brings together the latest advances in perturbation signal design. It describes the approaches to the design process that are relevant to industries. The authors’ discussion of several software packages (Frequency Domain System Identification Toolbox, prs, GALOIS, multilev_new, and Input-Signal-Creator) will allow readers to understand the different designs in industries and begin designing common classes of signals. The authors include two case studies that provide a balance between the theory and practice of these designs: the identification of a direction-dependent electronic nose system; and the identification of a multivariable cooling system with time-varying delay. Major aspects of signal design such as the formulation of suitable specifications in the face of practical constraints, the classes of designs available, the various objectives necessitating separate treatments when dealing with nonlinear systems, and extension to multi-input scenarios, are discussed. Codes, including some that will produce simulated data, are included to help readers replicate the results described. Industrial Process Identification is a powerful source of information for control engineers working in the process and communications industries seeking guidance on choosing identification software tools for use in practical experiments and case studies. The book will also be of interest to academic researchers and students working in electrical, mechanical and communications engineering and the application of perturbation signal design. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.


Advanced Process Identification and Control

Advanced Process Identification and Control

Author: Enso Ikonen

Publisher: CRC Press

Published: 2001-10-02

Total Pages: 336

ISBN-13: 9780824706487

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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.


PID Control

PID Control

Author: Michael A Johnson

Publisher: Springer Science & Business Media

Published: 2005-12-28

Total Pages: 559

ISBN-13: 1846281482

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The effectiveness of proportional-integral-derivative (PID) controllers for a large class of process systems has ensured their continued and widespread use in industry. Similarly there has been a continued interest from academia in devising new ways of approaching the PID tuning problem. To the industrial engineer and many control academics this work has previously appeared fragmented; but a key determinant of this literature is the type of process model information used in the PID tuning methods. PID Control presents a set of coordinated contributions illustrating methods, old and new, that cover the range of process model assumptions systematically. After a review of PID technology, these contributions begin with model-free methods, progress through non-parametric model methods (relay experiment and phase-locked-loop procedures), visit fuzzy-logic- and genetic-algorithm-based methods; introduce a novel subspace identification method before closing with an interesting set of parametric model techniques including a chapter on predictive PID controllers. Highlights of PID Control include: an introduction to PID control technology features and typical industrial implementations; chapter contributions ordered by the increasing quality of the model information used; novel PID control concepts for multivariable processes. PID Control will be useful to industry-based engineers wanting a better understanding of what is involved in the steps to a new generation of PID controller techniques. Academics wishing to have a broader perspective of PID control research and development will find useful pedagogical material and research ideas in this text.


Modelling and Control of Dynamic Systems Using Gaussian Process Models

Modelling and Control of Dynamic Systems Using Gaussian Process Models

Author: Juš Kocijan

Publisher: Springer

Published: 2015-11-21

Total Pages: 281

ISBN-13: 3319210211

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This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.


Process Modelling for Control

Process Modelling for Control

Author: Benoît Codrons

Publisher: Springer Science & Business Media

Published: 2005-12-28

Total Pages: 255

ISBN-13: 1846282470

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Process Modelling for Control concentrates on the modelling steps underlying a successful control design, answering questions like: How should I carry out the identification of my process to obtain a good model? How can I assess the quality of a model before to using it in control design? How can I ensure that a controller will stabilise a real process well enough before implementation? What is the most efficient method of order reduction to simplify the implementation of high-order controllers? System identification, model/controller validation and order reduction are studied in a common framework. Detailed worked examples, representative of various industrial applications, are given. This monograph uses mathematics convenient to researchers interested in real applications and to practising engineers interested in control theory. It enables control engineers to improve their methods and provides academics and graduate students with an all-round view of recent results in modelling for control.


Process Control Engineering

Process Control Engineering

Author: A. Ramachandro. Rao

Publisher: CRC Press

Published: 1993-10-21

Total Pages: 432

ISBN-13: 9782881246289

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"Computer-aided instruction technology has been used here as an educational tool. A user-friendly computer software package, "Process Control Engineering Teachware" (PCET) is available on a diskette..." - Pref.