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Linear And Nonlinear Distributed Economic Model Predictive Control


Linear And Nonlinear Distributed Economic Model Predictive Control
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Linear And Nonlinear Distributed Economic Model Predictive Control


Linear And Nonlinear Distributed Economic Model Predictive Control
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Author : Jaehwa Lee
language : en
Publisher:
Release Date : 2013

Linear And Nonlinear Distributed Economic Model Predictive Control written by Jaehwa Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.




Distributed And Economic Model Predictive Control Beyond Setpoint Stabilization


Distributed And Economic Model Predictive Control Beyond Setpoint Stabilization
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Author : Matthias A. Müller
language : en
Publisher: Logos Verlag Berlin GmbH
Release Date : 2014

Distributed And Economic Model Predictive Control Beyond Setpoint Stabilization written by Matthias A. Müller and has been published by Logos Verlag Berlin GmbH this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Mathematics categories.


In this thesis, we study model predictive control (MPC) schemes for control tasks which go beyond the classical objective of setpoint stabilization. In particular, we consider two classes of such control problems, namely distributed MPC for cooperative control in networks of multiple interconnected systems, and economic MPC, where the main focus is on the optimization of some general performance criterion which is possibly related to the economics of a system. The contributions of this thesis are to analyze various systems theoretic properties occurring in these type of control problems, and to develop distributed and economic MPC schemes with certain desired (closed-loop) guarantees. To be more precise, in the field of distributed MPC we propose different algorithms which are suitable for general cooperative control tasks in networks of interacting systems. We show that the developed distributed MPC frameworks are such that the desired cooperative goal is achieved, while coupling constraints between the systems are satisfied. Furthermore, we discuss implementation and scalability issues for the derived algorithms, as well as the necessary communication requirements between the systems. In the field of economic MPC, the contributions of this thesis are threefold. Firstly, we analyze a crucial dissipativity condition, in particular its necessity for optimal steady-state operation of a system and its robustness with respect to parameter changes. Secondly, we develop economic MPC schemes which also take average constraints into account. Thirdly, we propose an economic MPC framework with self-tuning terminal cost and a generalized terminal constraint, and we show how self-tuning update rules for the terminal weight can be derived such that desirable closed-loop performance bounds can be established.



Economic Nonlinear Model Predictive Control


Economic Nonlinear Model Predictive Control
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Author : Timm Faulwasser
language : en
Publisher:
Release Date : 2018

Economic Nonlinear Model Predictive Control written by Timm Faulwasser and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Electronic books categories.


In recent years, Economic Model Predictive Control (EMPC) has received considerable attention of many research groups. The present tutorial survey summarizes state-of-the-art approaches in EMPC. In this context EMPC is to be understood as receding-horizon optimal control with a stage cost that does not simply penalize the distance to a desired equilibrium but encodes more sophisticated economic objectives. This survey provides a comprehensive overview of EMPC stability results: with and without terminal constraints, with and without dissipativity assumptions, with averaged constraints, formulations with multiple objectives and generalized terminal constraints as well as Lyapunov-based approaches.



Distributed Model Predictive Control Made Easy


Distributed Model Predictive Control Made Easy
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Author : José M. Maestre
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-10

Distributed Model Predictive Control Made Easy written by José M. Maestre 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 2013-11-10 with Technology & Engineering categories.


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.



Handbook Of Model Predictive Control


Handbook Of Model Predictive Control
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Author : Saša V. Raković
language : en
Publisher: Springer
Release Date : 2018-09-01

Handbook Of Model Predictive Control written by Saša V. Raković and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-01 with Science categories.


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.



Economic Model Predictive Control


Economic Model Predictive Control
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Author : Helen Durand
language : en
Publisher: Foundations and Trends (R) in Systems and Control
Release Date : 2018-06-19

Economic Model Predictive Control written by Helen Durand and has been published by Foundations and Trends (R) in Systems and Control this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-19 with categories.


Economic Model Predictive Control (EMPC) is a control strategy that moves process operation away from the steady-state paradigm toward a potentially time-varying operating strategy to improve process profitability. The EMPC literature is replete with evidence that this new paradigm may enhance process profits when a model of the chemical process provides a sufficiently accurate representation of the process dynamics. Systems using EMPC often neglect the dynamics associated with equipment and are often neglected when modeling a chemical process. Recent studies have shown they can significantly impact the effectiveness of an EMPC system. Concentrating on valve behavior in a chemical process, this monograph develops insights into the manner in which equipment behavior should impact the design process for EMPC and to provide a perspective on a number of open research topics in this direction. Written in tutorial style, this monograph provides the reader with a full literature review of the topic and demonstrates how these techniques can be adopted in a practical system.



Model Predictive Control Of Microgrids


Model Predictive Control Of Microgrids
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Author : Carlos Bordons
language : en
Publisher: Springer Nature
Release Date : 2019-09-12

Model Predictive Control Of Microgrids written by Carlos Bordons and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-12 with Technology & Engineering categories.


The book shows how the operation of renewable-energy microgrids can be facilitated by the use of model predictive control (MPC). It gives readers a wide overview of control methods for microgrid operation at all levels, ranging from quality of service, to integration in the electricity market. MPC-based solutions are provided for the main control issues related to energy management and optimal operation of microgrids. The authors present MPC techniques for case studies that include different renewable sources – mainly photovoltaic and wind – as well as hybrid storage using batteries, hydrogen and supercapacitors. Experimental results for a pilot-scale microgrid are also presented, as well as simulations of scheduling in the electricity market and integration of electric and hybrid vehicles into the microgrid. in order to replicate the examples provided in the book and to develop and validate control algorithms on existing or projected microgrids. Model Predictive Control of Microgrids will interest researchers and practitioners, enabling them to keep abreast of a rapidly developing field. The text will also help to guide graduate students through processes from the conception and initial design of a microgrid through its implementation to the optimization of microgrid management. 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.



Economic Model Predictive Control


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.



Model Predictive Control


Model Predictive Control
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Author : James Blake Rawlings
language : en
Publisher:
Release Date : 2024

Model Predictive Control written by James Blake Rawlings and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.




Distributed Cooperative Model Predictive Control Of Networked Systems


Distributed Cooperative Model Predictive Control Of Networked Systems
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Author : Yuanyuan Zou
language : en
Publisher: Springer Nature
Release Date : 2022-10-03

Distributed Cooperative Model Predictive Control Of Networked Systems written by Yuanyuan Zou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-03 with Technology & Engineering categories.


This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectiveness of the event-triggering mechanism and how to improve the event-triggered DMPC for different requirements improvement of control performance, extension to interconnected networked systems, etc. The book is likely to be of interest to the persons who are engaged in researching control theory in academic institutes, the persons who go in for developing control systems in R&D institutes or companies, the control engineers who are engaged in the implementation of control algorithms, and people who are interested in the distributed MPC.