Advanced Practical Process Control
Published on 19. September 2003
Book
Hardback
IX, 309 pages
978-3-540-40480-4 (ISBN)
Description
In the process industries there is an ongoing need for improvement of the opera tion of the process. One of the disciplines that will help the process engineer to achieve this is process control. There are many industrial automation systems to day that will offer powerful tools to meet the process control needs of industries with continuous, batch and discrete operations. Advanced control solutions sustain and improve the plant's competitiveness by ensuring: - safe operations - compliance with environmental regulations - effective use ofraw materials and energy - efficient production - manufacturing ofhigh quality products - flexible accommodation ofchanging process requirements This book was written from the perspective of introducing advanced control con cepts, which can help the engineer to reach the aforementioned goals. Many ad vanced control techniques have been implemented in industry in recent years, since hardware and software platforms are becoming increasingly powerful. Manufacturers ofprocess control equipment call this hardware and software envi ronment generally 'distributed control system'. The distributed control system equipment offers the engineer an excellent plat form for writing and implementing advanced control solutions. However, most large chemical and petrochemical manufacturers hire control specialists to imple ment these control solutions, while small manufacturers often lack the funds to hire these professionals. Therefore it is our experience that in the latter case, proc ess engineers often write the control programs required to improve process opera tion.
Reviews / Votes
From the reviews:"The book Advanced Practical Process Control by Roffel and Betlem complements the textbook literature in the field of process control with a solution oriented approach. . The approach is very practical and solution oriented. It aims at familiarizing the reader with essential concepts of advanced process control as they are employed nowadays in the process industries. . the book definitely does enrich the textbook literature on process control. . The target audience is indeed the industrial practitioner or the chemical engineering student . ." (W. Marquardt, International Journal of Robust and Nonlinear Control, Vol. 16 (2), 2006)"This book is to help the process engineer to start from the available theory and to build control solutions. . Having some theoretical background in process dynamics, identification and optimal control, this book . will help the process engineer to solve control problems for process improvement tasks in practice." (Kurt Marti, Zentralblatt MATH, Vol. 1042 (17), 2004)"The book Advanced Practical Process Control . has been written for senior and graduate students as a comprehensive textbook on advanced process control with a solution-oriented approach. . The book covers a large array of process-control solutions. . The book is extremely well organized. Each chapter . gives a clear summary of what is to be described. . illustrated by numerous pictures, plots, and flow diagrams. . The presentations are clear, and the concepts and ideas are illustrated extremely well through numerous, interesting examples." (Luige Vladareanu, International Journal of Acoustics and Vibration, Vol. 14 (3), 2009)More details
Edition
2004 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Primary & secondary/elementary & high school
Graduate
Illustrations
IX, 309 p. With online files/update.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
644 gr
ISBN-13
978-3-540-40480-4 (9783540404804)
DOI
10.1007/978-3-642-18258-7
Schweitzer Classification
Other editions
Additional editions
Brian Roffel | Ben Betlem
Advanced Practical Process Control
Book
11/2013
Springer
€53.49
Shipment within 7-9 days
Content
1 Introduction to Advanced Process Control Concepts.- 1.1 Process Time Constant.- 1.2 Domain Transformations.- 1.3 Laplace Transformation.- 1.4 Discrete Approximations.- 1.5 z-Transforms.- 1.6 Advanced and Modified z-Transforms.- 1.7 Common Elements in Control.- 1.8 The Smith Predictor.- 1.9 Feed-forward Control.- 1.10 Feed-forward Control in a Smith Predictor.- 1.11 Dahlin's Control Algorithm.- References.- 2 Process Simulation.- 2.1 Simulation using Matlab Simulink.- 2.2 Simulation of Feed-forward Control.- 2.3 Control Simulation of a 2x2 System.- 2.4 Simulation of Dahlin's Control Algorithm.- 3 Process Modeling and Identification.- 3.1 Model Applications.- 3.2 Types of Models.- 3.3 Empirical (linear) Dynamic Models.- 3.4 Model Structure Considerations.- 3.5 Model Identification.- References.- 4 Identification Examples.- 4.1 SISO Furnace Parametric Model Identification.- 4.2 MISO Parametric Model Identification.- 4.3 MISO Non-parametric Identification of a Non-integrating Process.- 4.4 MIMO Identification of an Integrating and Non-integrating Process.- 4.5 Design of Plant Experiments.- 4.5.1 Nature of Input Sequence.- 4.5.2 PRBS Type Input.- 4.5.3 Step Type Input.- 4.5.4 Type of Experiment.- 4.6 Data File Layout.- 4.7 Conversion of Model Structures.- 4.8 Example and Comparison of Open and Closed Loop Identification.- References.- 5 Linear Multivariable Control.- 5.1 Interaction in Multivariable Systems.- 5.2 Dynamic Matrix Control.- 5.3 Properties of Commercial MPC Packages.- References.- 6 Multivariable Optimal Constraint Control Algorithm.- 6.1 General Overview.- 6.2 Model Formulation for Systems with Dead Time.- 6.3 Model Formulation for Multivariable Processes.- 6.4 Model Formulation for Multivariable Processes with Time Delays.- 6.5 Model Formulation in Caseof a Limited Control Horizon.- 6.6 Mocca Control Formulation.- 6.7 Non-linear Transformations.- 6.8 Practical Implementation Guidelines.- 6.9 Case Study.- 6.10 Control of a Fluidized Catalytic Cracker.- 6.11 Examples of Case Studies in MATLAB.- 6.12 Control of Integrating Processes.- 6.13 Lab Exercises.- 6.14 Use of MCPC for Constrained Multivariable Control.- References.- 7 Internal Model Control.- 7.1 Introduction.- 7.2 Factorization of Multiple Delays.- 7.3 Filter Design.- 7.4 Feed-forward IMC.- 7.5 Example of Controller Design.- 7.6 LQ Optimal Inverse Design.- References.- 8 Nonlinear Multivariable Control.- 8.1 Non-linear Model Predictive Control.- 8.2 Non-linear Quadratic DMC.- 8.3 Generic Model Control.- 8.4 Problem Description.- 8.5 GMC Application to the CSTR System.- 8.6 Discussion of the GMC Algorithm.- 8.7 Simulation of Reactor Control.- 8.8 One Step Reference Trajectory Control.- 8.9 Predictive Horizon Reference Trajectory Control.- References.- 9 Optimization of Process Operation.- 9.1 Introduction to Real-time Optimization.- 9.2 Model Building.- 9.3 The Objective Function.- 9.4 Unconstrained Functions: one Dimensional Problems.- 9.5 Unconstrained Multivariable Optimization.- 9.6 Linear Programming.- 9.7 Non-linear Programming.- References.- 10 Optimization Examples.- 10.1 AMPL: a Multi-purpose Optimizer.- 10.2 Optimization Examples.- References.- 11 Integration of Control and Optimization.- 11.1 Introduction.- 11.2 Description of the Desalination Plant.- 11.3 Production Maximization of Desalination Plant.- 11.4 Linear Model Predictive Control of Desalination Plant.- 11.5 Reactor problem definition.- 11.6 Multivariable Non-linear Control of the Reactor.- References.- Appendix I. MCPC software guide.- I.1 Installation.- I.2 Model identification.- I.2.1 General process information.- I.2.2 Identification data.- I.2.3 Output details.- I.3 Controller design.- I.4 Control simulation.- I.5 Dealing with constraints.- I.6 Saving a project.- Appendix II. Comparison of control strategies for a hollow shaft reactor.- II.1 Introduction.- II.2 Model Equations.- II.3 Proportional Integral Control.- II.4 Linear Multivariable Control.- II.5 Non-linear Multivariable Control.- References.