Robust Model Predictive Control Design

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Robust Model Predictive Control Design

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Author : Geoffrey Laurence Bell
language : en
Publisher:
Release Date : 2000

Robust Model Predictive Control Design written by Geoffrey Laurence Bell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.

Robust Model Predictive Control Design

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Author : Vojtech Vesely
language : en
Publisher:
Release Date : 2010

Robust Model Predictive Control Design written by Vojtech Vesely and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

Robust Model Predictive Control For Large Scale Manufacturing Systems Subject To Uncertainties

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Author : Jens Tonne
language : en
Publisher: kassel university press GmbH
Release Date : 2018-01-19

Robust Model Predictive Control For Large Scale Manufacturing Systems Subject To Uncertainties written by Jens Tonne and has been published by kassel university press GmbH this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-19 with categories.

Large scale manufacturing systems are often run with constant process parameters although continuous and abrupt disturbances influence the process. To reduce quality variations and scrap, a closed-loop control of the process variables becomes indispensable. In this thesis, a modeling and control framework for multistage manufacturing systems is developed, in which the systems are subject to abrupt faults, such as component defects, and continuous disturbances. In this context, three main topics are considered: the development of a modeling framework, the design of robust distributed controllers, and the application of both to the models of a real hot stamping line. The focus of all topics is on the control of the product properties considering the available knowledge of faults and disturbances.

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.

Robust Model Predictive Control

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Author : Yiyang Wang
language : en
Publisher:
Release Date : 2002

Robust Model Predictive Control written by Yiyang Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.

Nonlinear Model Predictive Control

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Author : Lalo Magni
language : en
Publisher: Springer
Release Date : 2009-05-18

Nonlinear Model Predictive Control written by Lalo Magni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-18 with Technology & Engineering categories.

Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.

Control Systems Design 2003 Csd 03

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Author : Stefan Kozak
language : en
Publisher: Elsevier
Release Date : 2004-04

Control Systems Design 2003 Csd 03 written by Stefan Kozak and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04 with Science categories.

The material presented in this volume represents current ideas, knowledge, experience and research results in various fields of control system design.

Model Predictive Control

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Author : Baocang Ding
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-25

Model Predictive Control written by Baocang Ding 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 2024-03-25 with Science categories.

Model Predictive Control Understand the practical side of controlling industrial processes Model Predictive Control (MPC) is a method for controlling a process according to given parameters, derived in many cases from empirical models. It has been widely applied in industrial units to increase revenue and promoting sustainability. Systematic overviews of this subject, however, are rare, and few draw on direct experience in industrial settings. Assuming basic knowledge of the relevant mathematical and algebraic modeling techniques, the book’s title combines foundational theories of MPC with a thorough sense of its practical applications in an industrial context. The result is a presentation uniquely suited to rapid incorporation in an industrial workplace. Model Predictive Control readers will also find: Two-part organization to balance theory and applications Selection of topics directly driven by industrial demand An author with decades of experience in both teaching and industrial practice This book is ideal for industrial control engineers and researchers looking to understand MPC technology, as well as advanced undergraduate and graduate students studying predictive control and related subjects.

Power Plants And Power Systems Control 2003

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Author : Kwang Y Lee
language : en
Publisher: Elsevier
Release Date : 2004-04

Power Plants And Power Systems Control 2003 written by Kwang Y Lee and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04 with Science categories.

Approx. 422 pages

Adaptive Robust Model Predictive Control For Nonlinear Systems

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Author : Brett Thomas Lopez
language : en
Publisher:
Release Date : 2019

Adaptive Robust Model Predictive Control For Nonlinear Systems written by Brett Thomas Lopez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as tube MPC, uses a robust controller (designed offline) to keep the system in an invariant tube centered around a desired nominal trajectory (generated online). While tube MPC regains tractability, there are several theoretical and practical problems that must be solved for it to be used in real-world scenarios. First, the decoupled trajectory and control design is inherently suboptimal, especially for systems with changing objectives or operating conditions. Second, no existing tube MPC framework is able to capture state-dependent uncertainty due to the complexity of calculating invariant tubes, resulting in overly-conservative approximations. And third, the inability to reduce state-dependent uncertainty through online parameter adaptation/estimation leads to systematic error in the trajectory design. This thesis aims to address these limitations by developing a computationally tractable nonlinear tube MPC framework that is applicable to a broad class of nonlinear systems.