Practical Design and Application of Model Predictive Control

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Author :
Publisher : Butterworth-Heinemann
ISBN 13 : 0128139196
Total Pages : 262 pages
Book Rating : 4.96/5 ( download)

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Book Synopsis Practical Design and Application of Model Predictive Control by : Nassim Khaled

Download or read book Practical Design and Application of Model Predictive Control written by Nassim Khaled and published by Butterworth-Heinemann. This book was released on 2018-05-04 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino®. The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB® and Simulink® codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com. Illustrates how to design, tune and deploy MPC for projects in a quick manner Demonstrates a variety of applications that are solved using MATLAB® and Simulink® Bridges the gap in providing a number of realistic problems with very hands-on training Provides MATLAB® and Simulink® code solutions. This includes nonlinear plant models that the reader can use for other projects and research work Presents application problems with solutions to help reinforce the information learned

Model Predictive Control System Design and Implementation Using MATLAB®

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 1848823312
Total Pages : 398 pages
Book Rating : 4.10/5 ( download)

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Book Synopsis Model Predictive Control System Design and Implementation Using MATLAB® by : Liuping Wang

Download or read book Model Predictive Control System Design and Implementation Using MATLAB® written by Liuping Wang and published by Springer Science & Business Media. This book was released on 2009-02-14 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.

Model Predictive Control in the Process Industry

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Publisher : Springer Science & Business Media
ISBN 13 : 1447130081
Total Pages : 250 pages
Book Rating : 4.86/5 ( download)

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Book Synopsis Model Predictive Control in the Process Industry by : Eduardo F. Camacho

Download or read book Model Predictive Control in the Process Industry written by Eduardo F. Camacho and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Automotive Model Predictive Control

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Publisher : Springer
ISBN 13 : 1849960712
Total Pages : 291 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Automotive Model Predictive Control by : Luigi Del Re

Download or read book Automotive Model Predictive Control written by Luigi Del Re and published by Springer. This book was released on 2010-03-11 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility – at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for “slow” complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for “fast”systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.

Predictive Control for Linear and Hybrid Systems

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Author :
Publisher : Cambridge University Press
ISBN 13 : 1107016886
Total Pages : 447 pages
Book Rating : 4.80/5 ( download)

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Book Synopsis Predictive Control for Linear and Hybrid Systems by : Francesco Borrelli

Download or read book Predictive Control for Linear and Hybrid Systems written by Francesco Borrelli and published by Cambridge University Press. This book was released on 2017-06-22 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

Model Predictive Control

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Publisher : Springer Science & Business Media
ISBN 13 : 0857293982
Total Pages : 405 pages
Book Rating : 4.85/5 ( download)

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Book Synopsis Model Predictive Control by : Eduardo F. Camacho

Download or read book Model Predictive Control written by Eduardo F. Camacho and published by Springer Science & Business Media. This book was released on 2013-01-10 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. The book demonstrates that a powerful technique does not always require complex control algorithms. Many new exercises and examples have also been added throughout. Solutions available for download from the authors' website save the tutor time and enable the student to follow results more closely even when the tutor isn't present.

Model Predictive Control

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Publisher :
ISBN 13 : 9780975937754
Total Pages : 770 pages
Book Rating : 4.58/5 ( download)

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Book Synopsis Model Predictive Control by : James Blake Rawlings

Download or read book Model Predictive Control written by James Blake Rawlings and published by . This book was released on 2017 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Economic Model Predictive Control

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Author :
Publisher : Springer
ISBN 13 : 331941108X
Total Pages : 311 pages
Book Rating : 4.88/5 ( download)

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Book Synopsis Economic Model Predictive Control by : Matthew Ellis

Download or read book Economic Model Predictive Control written by Matthew Ellis and published by Springer. This book was released on 2016-07-27 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes.In addition to being mathematically rigorous, these methods accommodate key practical issues, for example, direct optimization of process economics, time-varying economic cost functions and computational efficiency. Numerous comments and remarks providing fundamental understanding of the merging of process economics and feedback control into a single framework are included. A control engineer can easily tailor the many detailed examples of industrial relevance given within the text to a specific application. The authors present a rich collection of new research topics and references to significant recent work making Economic Model Predictive Control an important source of information and inspiration for academics and graduate students researching the area and for process engineers interested in applying its ideas.

Nonlinear Model Predictive Control

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Publisher : Birkhäuser
ISBN 13 : 3034884079
Total Pages : 463 pages
Book Rating : 4.75/5 ( download)

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Book Synopsis Nonlinear Model Predictive Control by : Frank Allgöwer

Download or read book Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Model-Based Predictive Control

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Author :
Publisher : CRC Press
ISBN 13 : 135198859X
Total Pages : 265 pages
Book Rating : 4.99/5 ( download)

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Book Synopsis Model-Based Predictive Control by : J.A. Rossiter

Download or read book Model-Based Predictive Control written by J.A. Rossiter and published by CRC Press. This book was released on 2017-07-12 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.