Book Description
From power plants to sugar refining, model predictive control (MPC) schemes have established themselves as the preferred control strategies for a wide variety of processes.
The second edition of
Model Predictive Control provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners.
Model Predictive Control demonstrates that a powerful technique does not always require complex control algorithms.
The text features material on the following subjects:
• general MPC elements and algorithms;
• commercial MPC schemes;
• generalized predictive control
• multivariable, robust, constrained nonlinear and hybrid MPC;
• fast methods for MPC implementation;
• applications.
All of the material is thoroughly updated for the second edition with the chapters on nonlinear MPC, MPC and hybrid systems and MPC implementation being entirely new. Many new exercises and examples have also have also been added throughout and MATLAB
® programs to aid in their solution can be downloaded from the authors' website. The text is an excellent aid for graduate and advanced undergraduate students and will also be of use to researchers and industrial practitioners wishing to keep abreast of a fast-moving field.
Customer Reviews:
A good book.......2000-12-05
excelent inside on predictive control
Book Description
Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.
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Nonlinear Model Predictive Control (Progress in Systems and Control Theory)
Manufacturer: Birkhäuser Basel
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The IMO Compendium: A Collection of Problems Suggested for The International Mathematical Olympiads: 1959-2004 (Problem Books in Mathematics)
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The Geometer's Sketchpad (R): Student Edition
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Trigonometry
ASIN: 3764362979 |
Book Description
During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland.
The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.
Customer Reviews:
A fine book.......2000-12-05
Good inside of nonlinear control.
Book Description
Building on the knowledge and the goals of the best-selling book, Advanced Control Unleashed, this portable pocket guide goes beyond theoretical concepts and provides new insight into the implementation practices after the objectives have been defined and the technology decisions have been made.
Recognizing the opportunity that models present to capture and exploit plant knowledge, the authors share their expertise on the concepts, procedures, and examples needed to construct and apply different models through the use of "state of the art" software for simulation and model predictive control.
You don't need an advanced degree to get the most out of this pocket guide. Models Unleashed will help engineers closest to the application take advantage of their experience by embedding it in a model and a control system.
Customer Reviews:
A practical pocket guide to Model-Based Control Applications.......2006-07-11
This pocket guide is intended to provide users with a concise presentation of the concepts, procedures and examples they will need to construct and apply both small models (e.g. first order model obtained from step tests) and large models (e.g. a first-principle model that is based on mass and energy balances), using state-of-the-art software for simulation and model predictive control.
This guide contains details, data, and test results that are yet not available in the literature. The user doesn't need to have an advanced degree to get the most out of this guide.
Building on the knowledge and the goals of the authors' best-selling book, Advanced Control Unleashed, this guide is designed to enable the engineers closest to the applications to exploit their experience by embedding it in a model and a control system.
I am an Industrial Practitioner of Process Control. I have been working for more than 16 years as an Instrumentation, Automation, and Process Safety and Control Engineer for the Oil & Gas Industry. I own both books, and I have found that together they are an excellent reference in my day to day activities.
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Advances in Model-Based Predictive Control (Oxford Science Publications)
Manufacturer: Oxford University Press, USA
ProductGroup: Book
Binding: Hardcover
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ASIN: 0198562926 |
Book Description
Model based predictive control (MBPC) is arguably the most important approach to the advance control of complex interacting industrial processes. Unique among modern theories, MBPC can handle real-time state and actuator constraints in a natural way, enabling plants to maximize their profits.
In addition, the wide range of model structures, prediction horizons, and optimization criteria allows for tailor-made MBPC applications--whether they be for high-speed machine tools or large-scale industrial processes. This timely edited volume, based on a conference held at Oxford University and
devoted exclusively to MBPC, brings the field up to date with the latest theoretical and practical advances. Topics include how MBPC is expanding to include variants in the basic themes (such as new prediction and optimization approaches, nonlinear models, and two-dimensional problems), general
stabilization ideas for constrained plant, and unsolved problems in MBPC. This excellent volume is the introduction to the theory, current applications, and hot research areas in MBPC that students and professionals in control systems have been waiting for.
Customer Reviews:
Contenido.......2004-05-10
Me parece que es un libro que tiene el contenido acertado para yo poderlo aplicar en mi trabajo de grado de Ingeniería en Instrumentación y Control.
Da ejemplos de casos reales muy claros y tiene una guia metodológica muy buena.
Product Description
Results of the international workshop entitled "Assesmentand Future Directions of Nonlinear Model Predictive Control (NMPC´05), which was held in Freudenstadt-Lauterbad, Germany on August 26-30, 2005
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Constrained Control and Estimation: An Optimisation Approach (Communications and Control Engineering)
Graham C. Goodwin ,
María M Seron , and
José A. De Doná
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
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ASIN: 1852335483 |
Book Description
Recent developments in constrained control and estimation have created a need for this comprehensive introduction to the underlying fundamental principles. These advances have significantly broadened the realm of application of constrained control.
- Using the principal tools of prediction and optimisation, examples of how to deal with constraints are given, placing emphasis on model predictive control.
- New results combine a number of methods in a unique way, enabling you to build on your background in estimation theory, linear control, stability theory and state-space methods.
- Companion web site, continually updated by the authors.
Easy to read and at the same time containing a high level of technical detail, this self-contained, new approach to methods for constrained control in design will give you a full understanding of the subject.
Product Description
This is a AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A086633. The abstract provided by the Pentagon follows: Recent research efforts have applied the receding horizon Model Predictive Control (MPC) strategy to linearized high performance aerospace systems. The research contained in this thesis used these recent results in order to apply the MPC strategy to a nonlinear high performance aerospace system, specifically an F-16 fighter aircraft model. The model was commanded to follow dynamic trajectories of roll angle and altitude. Further, adaptive constraint techniques were used to improve system tracking. To accomplish these tasks, code and block diagrams were generated using the commercial software packages of Matlab and Simulink. Numerous simulations were conducted with the goal of achieving realistic aircraft performance. In many cases, to improve system tracking and reduce control input oscillations, rigid mathematical constraints previously used in the MPC strategy were relaxed.
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Control of Dead-time Processes (Advanced Textbooks in Control and Signal Processing)
J.E. Normey-Rico , and
E.F. Camacho
Manufacturer: Springer
ProductGroup: Book
Binding: Paperback
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ASIN: 1846288282 |
Book Description
Industrial processes and engineering, economic and biological systems commonly exhibit time delays or dead times. Dead time complicates the analysis and design of control systems and makes satisfactory control more difficult.
Control of Dead-time Processes introduces the fundamental techniques for controlling dead-time processes ranging from simple monovariable to complex multivariable cases. Solutions to dead-time-process-control problems are studied using classical proportional-integral-differential (PID) control for the simpler examples and dead-time-compensator (DTC) and model predictive control (MPC) methods for progressively more complex ones. Although MPC and DTC approaches originate in different areas of control, both use predictors to overcome the effects of dead time. Using this fact, the text analyses MPC as a dead-time-compensation strategy and shows how it can be used synergistically with robust DTC tuning methodologies.
Graduate students working for their masters or PhDs in automatic control, chemical, electronic or mechanical engineering, in which dead-time processes are prevalent, will gain particular benefit from the following features of this text:
• interlinked study of PID, DTC and MPC for dead-time processes in a single source;
• exercises and further reading for each chapter;
• extensive use of illustrations, tables and examples;
• case studies based on real industrial problems with solutions that are simple to understand and easy to implement;
• MATLAB
® code developed by the authors to help analyse and control dead-time processes including code for all the examples in the book available for download from the Web.
Control of Dead-time Processes will also be of interest to control researchers and process control engineers. Chapters 1-8 of the text can be used as part of the final-year course for undergraduates in control or process engineering.
Product Description
This is a AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A380504. The abstract provided by the Pentagon follows: During the boost phase of ascent, winds have a significant impact on a launch vehicle's angle of attack, and can induce large structural loads on the vehicle. Traditional methods for mitigating these loads involve measuring the winds prior to launch and designing trajectories to minimize the vehicle angle of attack (0). The current balloon-based method of collecting wind field information produces wind profiles with significant uncertainty due to the inherent time delays associated with balloon measurement procedures. Managing the mission risk caused by these uncertain wind measurements has always been important to control system designers. This thesis will describe a novel approach to managing structural loads through the combination of a Light Detection and Ranging (LIDAR) wind sensor, and Model Predictive Control (MPC). LIDAR wind sensors can provide near real-time wind measurements, significantly reducing wind uncertainty at launch. MPC takes full advantage of this current wind information through a unique combination of proactive control, con-traint integration and tuning flexibility. This thesis describes the development of two types of MPC controllers, as well as a baseline controller representative of current control methods used by industry. A complete description of Model Predictive Control theory and derivation of the necessary control matrices is included. The performance of each MPC controller is compared to that of the baseline controller for a wide range of wind profiles from both the Eastern and Western U.S. Test Ranges.
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