Handbook Of Model Predictive Control

Author : Saša V. Raković,William S. Levine
Publisher : Springer
Page : 692 pages
File Size : 51,7 Mb
Release : 2018-09-01
Category : Science
ISBN : 9783319774893

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Handbook of Model Predictive Control by Saša V. Raković,William S. Levine Pdf

Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part of this book addresses the solution of optimization problems in “real” time for model-predictive control. The theory and applications of control theory often influence each other, so the last section of Handbook of Model Predictive Control rounds out the book with representative applications to automobiles, healthcare, robotics, and finance. The chapters in this volume will be useful to working engineers, scientists, and mathematicians, as well as students and faculty interested in the progression of control theory. Future developments in MPC will no doubt build from concepts demonstrated in this book and anyone with an interest in MPC will find fruitful information and suggestions for additional reading.

Author : Steve Bailey
Publisher : Unknown
Page : 0 pages
File Size : 41,8 Mb
Release : 2015-02-09
Category : Electronic
ISBN : 1632403536

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Model Predictive Control Handbook by Steve Bailey Pdf

This book provides elucidative information regarding Model Predictive Control (MPC). Model predictive control is that part of control algorithms in which a progressive method structure is utilized to foretell and improve process work. Also, it can be viewed as an expression demonstrating a typical restrain scheme that replicates the human thinking capability most efficiently. Nearly 50 years after its origin, it is vastly being welcomed in lot of spheres of engineering and is proving to be very advantageous. The book focuses on the latest developments in the field of MPC, in practice and theory, and structured in a way to provide in-depth knowledge to the practitioners and discoverers who want to gain information about the perimeters of MPC research. The book deals with the limits of MPC in theory and provides enough examples to enable us to understand them. It also portrays the practical usage of MPC in recent engineering spheres. As analytical and structural technology is growing rapidly, MPC will remain at the forefront even in the future.

Author : Basil Kouvaritakis,Mark Cannon
Publisher : Springer
Page : 384 pages
File Size : 50,5 Mb
Release : 2015-12-01
Category : Technology & Engineering
ISBN : 9783319248530

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Model Predictive Control by Basil Kouvaritakis,Mark Cannon Pdf

For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses.

Author : Ding Baocang
Publisher : CRC Press
Page : 117 pages
File Size : 45,7 Mb
Release : 2018-10-03
Category : Technology & Engineering
ISBN : 9781439859674

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Modern Predictive Control by Ding Baocang Pdf

Modern Predictive Control explains how MPC differs from other control methods in its implementation of a control action. Most importantly, MPC provides the flexibility to act while optimizing—which is essential to the solution of many engineering problems in complex plants, where exact modeling is impossible. The superiority of MPC is in its numerical solution. Usually, MPC is employed to solve a finite-horizon optimal control problem at each sampling instant and obtain control actions for both the present time and a future period. However, only the current control move is applied to the plant. This complete, step-by-step exploration of various approaches to MPC: Introduces basic concepts of systems, modeling, and predictive control, detailing development from classical MPC to synthesis approaches Explores use of Model Algorithmic Control (MAC), Dynamic Matrix Control (DMC), Generalized Predictive Control (GPC), and Two-Step Model Predictive Control Identifies important general approaches to synthesis Discusses open-loop and closed-loop optimization in synthesis approaches Covers output feedback synthesis approaches with and without a finite switching horizon This book gives researchers a variety of models for use with one- and two-step control. The author clearly explains the variations between predictive control methods—and the root of these differences—to illustrate that there is no one ideal MPC and that one should remain open to selecting the best possible model in each unique circumstance.

Author : Liuping Wang
Publisher : Springer Science & Business Media
Page : 378 pages
File Size : 40,9 Mb
Release : 2009-02-14
Category : Technology & Engineering
ISBN : 9781848823310

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Model Predictive Control System Design and Implementation Using MATLAB® by Liuping Wang Pdf

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.

Author : José M. Maestre,Rudy R. Negenborn
Publisher : Springer Science & Business Media
Page : 601 pages
File Size : 51,8 Mb
Release : 2013-11-10
Category : Technology & Engineering
ISBN : 9789400770065

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Distributed Model Predictive Control Made Easy by José M. Maestre,Rudy R. Negenborn Pdf

The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those who want to gain a deeper insight in the wide range of distributed MPC techniques available.

Author : Nassim Khaled,Bibin Pattel
Publisher : Butterworth-Heinemann
Page : 262 pages
File Size : 40,8 Mb
Release : 2018-05-04
Category : Technology & Engineering
ISBN : 9780128139196

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Practical Design and Application of Model Predictive Control by Nassim Khaled,Bibin Pattel Pdf

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

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 49,6 Mb
Release : 2010
Category : Electronic
ISBN : 9533071028

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Model Predictive Control by Anonim Pdf

Author : James Blake Rawlings,David Q. Mayne,Moritz Diehl
Publisher : Unknown
Page : 770 pages
File Size : 41,6 Mb
Release : 2017
Category : Control theory
ISBN : 0975937758

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Model Predictive Control by James Blake Rawlings,David Q. Mayne,Moritz Diehl Pdf

Author : Eduardo F. Camacho,Carlos Bordons Alba
Publisher : Springer Science & Business Media
Page : 405 pages
File Size : 40,6 Mb
Release : 2013-01-10
Category : Technology & Engineering
ISBN : 9780857293985

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Model Predictive Control by Eduardo F. Camacho,Carlos Bordons Alba Pdf

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.

Author : Lars Grüne,Jürgen Pannek
Publisher : Springer Science & Business Media
Page : 364 pages
File Size : 40,7 Mb
Release : 2011-04-11
Category : Technology & Engineering
ISBN : 9780857295019

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Nonlinear Model Predictive Control by Lars Grüne,Jürgen Pannek Pdf

Nonlinear Model Predictive Control is a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. An appendix covering NMPC software and accompanying software in MATLAB® and C++(downloadable from www.springer.com/ISBN) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.

Author : Tao Zheng
Publisher : BoD – Books on Demand
Page : 434 pages
File Size : 48,6 Mb
Release : 2011-07-05
Category : Technology & Engineering
ISBN : 9789533072982

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Advanced Model Predictive Control by Tao Zheng Pdf

Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in this area. The first part of this exciting book will help you comprehend the frontiers in theoretical research of MPC, such as Fast MPC, Nonlinear MPC, Distributed MPC, Multi-Dimensional MPC and Fuzzy-Neural MPC. In the second part, several excellent applications of MPC in modern industry are proposed and efficient commercial software for MPC is introduced. Because of its special industrial origin, we believe that MPC will remain energetic in the future.

Author : Timm Faulwasser,Matthias A. Müller,Karl Worthmann
Publisher : Springer Nature
Page : 250 pages
File Size : 53,5 Mb
Release : 2021-04-17
Category : Science
ISBN : 9783030632816

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Recent Advances in Model Predictive Control by Timm Faulwasser,Matthias A. Müller,Karl Worthmann Pdf

This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.

Author : Francesco Borrelli,Alberto Bemporad,Manfred Morari
Publisher : Cambridge University Press
Page : 447 pages
File Size : 49,8 Mb
Release : 2017-06-22
Category : Mathematics
ISBN : 9781107016880

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Predictive Control for Linear and Hybrid Systems by Francesco Borrelli,Alberto Bemporad,Manfred Morari Pdf

With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

Author : Sandip K. Lahiri
Publisher : John Wiley & Sons
Page : 309 pages
File Size : 49,6 Mb
Release : 2017-10-23
Category : Technology & Engineering
ISBN : 9781119243601

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Multivariable Predictive Control by Sandip K. Lahiri Pdf

A guide to all practical aspects of building, implementing, managing, and maintaining MPC applications in industrial plants Multivariable Predictive Control: Applications in Industry provides engineers with a thorough understanding of all practical aspects of multivariate predictive control (MPC) applications, as well as expert guidance on how to derive maximum benefit from those systems. Short on theory and long on step-by-step information, it covers everything plant process engineers and control engineers need to know about building, deploying, and managing MPC applications in their companies. MPC has more than proven itself to be one the most important tools for optimising plant operations on an ongoing basis. Companies, worldwide, across a range of industries are successfully using MPC systems to optimise materials and utility consumption, reduce waste, minimise pollution, and maximise production. Unfortunately, due in part to the lack of practical references, plant engineers are often at a loss as to how to manage and maintain MPC systems once the applications have been installed and the consultants and vendors’ reps have left the plant. Written by a chemical engineer with two decades of experience in operations and technical services at petrochemical companies, this book fills that regrettable gap in the professional literature. Provides a cost-benefit analysis of typical MPC projects and reviews commercially available MPC software packages Details software implementation steps, as well as techniques for successfully evaluating and monitoring software performance once it has been installed Features case studies and real-world examples from industries, worldwide, illustrating the advantages and common pitfalls of MPC systems Describes MPC application failures in an array of companies, exposes the root causes of those failures, and offers proven safeguards and corrective measures for avoiding similar failures Multivariable Predictive Control: Applications in Industry is an indispensable resource for plant process engineers and control engineers working in chemical plants, petrochemical companies, and oil refineries in which MPC systems already are operational, or where MPC implementations are being considering.