Practical Design And Application Of Model Predictive Control
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Practical Design And Application Of Model Predictive Control
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Author : Nassim Khaled
language : en
Publisher: Butterworth-Heinemann
Release Date : 2018-05-04
Practical Design And Application Of Model Predictive Control written by Nassim Khaled and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-04 with Technology & Engineering categories.
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
Modeling And Control Of Batch Processes
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Author : Prashant Mhaskar
language : en
Publisher: Springer
Release Date : 2018-11-28
Modeling And Control Of Batch Processes written by Prashant Mhaskar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-28 with Technology & Engineering categories.
Modeling and Control of Batch Processes presents state-of-the-art techniques ranging from mechanistic to data-driven models. These methods are specifically tailored to handle issues pertinent to batch processes, such as nonlinear dynamics and lack of online quality measurements. In particular, the book proposes: a novel batch control design with well characterized feasibility properties; a modeling approach that unites multi-model and partial least squares techniques; a generalization of the subspace identification approach for batch processes; and applications to several detailed case studies, ranging from a complex simulation test bed to industrial data. The book’s proposed methodology employs statistical tools, such as partial least squares and subspace identification, and couples them with notions from state-space-based models to provide solutions to the quality control problem for batch processes. Practical implementation issues are discussed to help readers understand the application of the methods in greater depth. The book includes numerous comments and remarks providing insight and fundamental understanding into the modeling and control of batch processes. Modeling and Control of Batch Processes includes many detailed examples of industrial relevance that can be tailored by process control engineers or researchers to a specific application. The book is also of interest to graduate students studying control systems, as it contains new research topics and references to significant recent work. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Model Based Predictive Control
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Author : J.A. Rossiter
language : en
Publisher: CRC Press
Release Date : 2017-07-12
Model Based Predictive Control written by J.A. Rossiter and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with Technology & Engineering categories.
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.
Model Predictive Control
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Author : Ridong Zhang
language : en
Publisher: Springer
Release Date : 2018-08-14
Model Predictive Control written by Ridong Zhang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-14 with Technology & Engineering categories.
This monograph introduces the authors’ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering.
Predictive Control
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Author : Yugeng Xi
language : en
Publisher: John Wiley & Sons
Release Date : 2019-07-02
Predictive Control written by Yugeng Xi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-02 with Technology & Engineering categories.
This book is a comprehensive introduction to model predictive control (MPC), including its basic principles and algorithms, system analysis and design methods, strategy developments and practical applications. The main contents of the book include an overview of the development trajectory and basic principles of MPC, typical MPC algorithms, quantitative analysis of classical MPC systems, design and tuning methods for MPC parameters, constrained multivariable MPC algorithms and online optimization decomposition methods. Readers will then progress to more advanced topics such as nonlinear MPC and its related algorithms, the diversification development of MPC with respect to control structures and optimization strategies, and robust MPC. Finally, applications of MPC and its generalization to optimization-based dynamic problems other than control will be discussed. Systematically introduces fundamental concepts, basic algorithms, and applications of MPC Includes a comprehensive overview of MPC development, emphasizing recent advances and modern approaches Features numerous MPC models and structures, based on rigorous research Based on the best-selling Chinese edition, which is a key text in China Predictive Control: Fundamentals and Developments is written for advanced undergraduate and graduate students and researchers specializing in control technologies. It is also a useful reference for industry professionals, engineers, and technicians specializing in advanced optimization control technology.
Advanced Model Predictive Control
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Author : Tao Zheng
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-07-05
Advanced Model Predictive Control written by Tao Zheng and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-05 with Technology & Engineering categories.
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.
Model Predictive Control
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Author : Eduardo F. Camacho
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-10
Model Predictive Control written by Eduardo F. Camacho and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-10 with Technology & Engineering categories.
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 In The Process Industry
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Author : Eduardo F. Camacho
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Model Predictive Control In The Process Industry written by Eduardo F. Camacho and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.
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.
Model Predictive Control
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Author : Eduardo F. Camacho
language : en
Publisher: Springer
Release Date : 2007-05-15
Model Predictive Control written by Eduardo F. Camacho and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-15 with Technology & Engineering categories.
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.
Economic Model Predictive Control
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Author : Matthew Ellis
language : en
Publisher: Springer
Release Date : 2016-07-27
Economic Model Predictive Control written by Matthew Ellis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-27 with Technology & Engineering categories.
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.
