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Author : Ivar Gustavsson
Publisher : Unknown
Page : 14 pages
File Size : 54,5 Mb
Release : 1974
Category : Electronic
ISBN : OCLC:186571687
Author : Zhiwen Chen
Publisher : Springer
Page : 112 pages
File Size : 52,7 Mb
Release : 2017-01-02
Category : Technology & Engineering
ISBN : 9783658167561
Zhiwen Chen aims to develop advanced fault detection (FD) methods for the monitoring of industrial processes. With the ever increasing demands on reliability and safety in industrial processes, fault detection has become an important issue. Although the model-based fault detection theory has been well studied in the past decades, its applications are limited to large-scale industrial processes because it is difficult to build accurate models. Furthermore, motivated by the limitations of existing data-driven FD methods, novel canonical correlation analysis (CCA) and projection-based methods are proposed from the perspectives of process input and output data, less engineering effort and wide application scope. For performance evaluation of FD methods, a new index is also developed.
Author : Tao Liu,Furong Gao
Publisher : Springer Science & Business Media
Page : 487 pages
File Size : 50,8 Mb
Release : 2011-11-16
Category : Technology & Engineering
ISBN : 9780857299772
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.
Author : Robert Haber,László Keviczky
Publisher : Springer Science & Business Media
Page : 432 pages
File Size : 54,7 Mb
Release : 1999
Category : Nonlinear theories
ISBN : 0792358562
Author : Chao Shang
Publisher : Springer
Page : 143 pages
File Size : 53,6 Mb
Release : 2018-02-22
Category : Technology & Engineering
ISBN : 9789811066771
This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.
Author : Dale E. Seborg,Thomas F. Edgar,Duncan A. Mellichamp,Francis J. Doyle, III
Publisher : John Wiley & Sons
Page : 512 pages
File Size : 44,7 Mb
Release : 2016-09-13
Category : Technology & Engineering
ISBN : 9781119285915
The new 4th edition of Seborg’s Process Dynamics Control provides full topical coverage for process control courses in the chemical engineering curriculum, emphasizing how process control and its related fields of process modeling and optimization are essential to the development of high-value products. A principal objective of this new edition is to describe modern techniques for control processes, with an emphasis on complex systems necessary to the development, design, and operation of modern processing plants. Control process instructors can cover the basic material while also having the flexibility to include advanced topics.
Author : Su Whan Sung,Jietae Lee,In-Beum Lee
Publisher : John Wiley & Sons
Page : 352 pages
File Size : 45,7 Mb
Release : 2009-07-23
Category : Science
ISBN : 0470824115
Process Identification and PID Control enables students and researchers to understand the basic concepts of feedback control, process identification, autotuning as well as design and implement feedback controllers, especially, PID controllers. The first The first two parts introduce the basics of process control and dynamics, analysis tools (Bode plot, Nyquist plot) to characterize the dynamics of the process, PID controllers and tuning, advanced control strategies which have been widely used in industry. Also, simple simulation techniques required for practical controller designs and research on process identification and autotuning are also included. Part 3 provides useful process identification methods in real industry. It includes several important identification algorithms to obtain frequency models or continuous-time/discrete-time transfer function models from the measured process input and output data sets. Part 4 introduces various relay feedback methods to activate the process effectively for process identification and controller autotuning. Combines the basics with recent research, helping novice to understand advanced topics Brings several industrially important topics together: Dynamics Process identification Controller tuning methods Written by a team of recognized experts in the area Includes all source codes and real-time simulated processes for self-practice Contains problems at the end of every chapter PowerPoint files with lecture notes available for instructor use
Author : Y. Zhu
Publisher : Elsevier
Page : 373 pages
File Size : 48,5 Mb
Release : 2001-10-08
Category : Technology & Engineering
ISBN : 9780080537115
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 : D. Bonvin
Publisher : Elsevier
Page : 561 pages
File Size : 41,8 Mb
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 9781483297590
This publication brings together the latest research findings in the key area of chemical process control; including dynamic modelling and simulation - modelling and model validation for application in linear and nonlinear model-based control: nonlinear model-based predictive control and optimization - to facilitate constrained real-time optimization of chemical processes; statistical control techniques - major developments in the statistical interpretation of measured data to guide future research; knowledge-based v model-based control - the integration of theoretical aspects of control and optimization theory with more recent developments in artificial intelligence and computer science.
Author : Yu-Chu Tian,Tonghua Zhang,Hongmei Yao,Moses O Tadé
Publisher : World Scientific
Page : 164 pages
File Size : 55,8 Mb
Release : 2014-05-29
Category : Mathematics
ISBN : 9789814616577
Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes. Thus, they provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios. Contents:IntroductionFundamentals of Process Modelling and Model ComputationFinite Difference Methods for Ordinary Differential Equation ModelsFinite Difference Methods for Partial Differential Equation ModelsWavelets-Based MethodsHigh Resolution MethodsComparative Studies of Numerical Methods for SMB Chromatographic ProcessesConclusion Readership: Students, academics and practitioners in the field of chemical engineering, numerical analysis and computational mathematics. Key Features:Comprehensive and representative examples and case studiesFocus on computational aspectsDeals with modelingStep-by-step procedures for industrial computingKeywords:Process Modeling;Model Computation;Numerical Computing;Process Systems Engineering;Process Dynamics;Complex Processes
Author : Paolo Mercorelli,Weicun Zhang,Hamidreza Nemati,YuMing Zhang
Publisher : Elsevier
Page : 486 pages
File Size : 52,8 Mb
Release : 2024-01-19
Category : Technology & Engineering
ISBN : 9780323952088
Modeling, Identification, and Control for Cyber-Physical Systems Towards Industry 4.0 studies and analyzes the role of algorithms in identifying and controlling such a system towards Industry 4.0, which is the digital transformation of manufacturing and related industries and value creation processes. This book focuses on the conception and implementation of intelligent algorithms. It will help readers who work on sensors, virtual sensors, actuators and virtual actuators embedded systems, network infrastructures, servers with computing and storage capacity, autonomous computing software, real-time data processing, and database graphical user interfaces wireless networking technologies. Cyber-Physical Systems are network components that coordinate physical actions with each other. These autonomous systems perceive their surroundings using virtual sensors and actively influence them via virtual actuators. Adaptable and continuously evolving, these systems free up skilled workers to perform complex tasks, avoiding productivity loss and re-work. Provides the new and cutting-edge research and development and a series of guidance procedures for potential applications from academic research to industrial R&D Focuses on the conception and implementation of intelligent algorithms Covers a wide spectrum of topics, including sensors, virtual sensors, actuators and virtual actuators embedded systems, network infrastructures, servers with computing and storage capacity, autonomous computing software, real-time data processing, and database graphical user interfaces wireless networking technologies
Author : Yucai Zhu,Ton Backx
Publisher : Unknown
Page : 0 pages
File Size : 51,6 Mb
Release : 1993
Category : Automatic control
ISBN : 0387198350
Author : Mohammad Shamsuzzoha
Publisher : BoD – Books on Demand
Page : 220 pages
File Size : 46,5 Mb
Release : 2018-09-12
Category : Technology & Engineering
ISBN : 9781789237009
PID Control for Industrial Processes presents a clear, multidimensional representation of proportional - integral - derivative (PID) control for both students and specialists working in the area of PID control. It mainly focuses on the theory and application of PID control in industrial processes. It incorporates recent developments in PID control technology in industrial practice. Emphasis has been given to finding the best possible approach to develop a simple and optimal solution for industrial users. This book includes several chapters that cover a broad range of topics and priority has been given to subjects that cover real-world examples and case studies. The book is focused on approaches for controller tuning, i.e., method bases on open-loop plant tests and closed-loop experiments.
Author : Biao Huang,Ramesh Kadali
Publisher : Springer Science & Business Media
Page : 249 pages
File Size : 48,5 Mb
Release : 2008-04-11
Category : Technology & Engineering
ISBN : 9781848002326
A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the predictor. Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a “data-driven” approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated.
Author : Andrew P. Featherstone,Jeremy G. VanAntwerp,Richard D. Braatz
Publisher : Springer Science & Business Media
Page : 177 pages
File Size : 44,7 Mb
Release : 2012-12-06
Category : Science
ISBN : 9781447104131
Sheet and film processes include coating, papermaking, metal rolling, and polymer film extrusion. Products produced by these processes include paper, bumper stickers, plastic bags, windshield safety glass, and sheet metal. The total capitalization of industries that rely on these processes is well over $ 500 billion worldwide. These processes are notorious for being difficult to control. The goal of this book is to present the theoretical background and practical techniques for the identification and control of sheet and film processes. It is explained why many existing industrial control systems perform poorly for sheet and film processes. Identification and control algorithms are described and illustrated which provide consistent and reliable product quality. These algorithms include an experimental design technique that ensures that informative data are collected during input-output experimentation, model identification techniques that produce a process model and an estimate of its accuracy, and control techniques that take into account actuator constraints as well as robustness to model uncertainties. The algorithms covered in this book are truly the state of the art. Variations on some of the algorithms have been implemented on industrial sheet and film processes. Other algorithms are in various stages of implementation. All of the algorithms have been applied to realistic simulation models constructed from industrial plant data; many of these studies are included in this book.
