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Developments in model-based optimization and control: distributed control and industrial applications

This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems,...

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Detalles Bibliográficos
Autores principales: Olaru, Sorin, Grancharova, Alexandra, Pereira, Fernando
Lenguaje:eng
Publicado: Springer 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-319-26687-9
http://cds.cern.ch/record/2120210
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author Olaru, Sorin
Grancharova, Alexandra
Pereira, Fernando
author_facet Olaru, Sorin
Grancharova, Alexandra
Pereira, Fernando
author_sort Olaru, Sorin
collection CERN
description This book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and design; and · applications to bioprocesses, multivehicle systems or energy management. The various contributions cover a subject spectrum including inverse optimality and more modern decentralized and cooperative formulations of receding-horizon optimal control. Readers will find fourteen chapters dedicated to optimization-based tools for robustness analysis, and decision-making in relation to feedback mechanisms—fault detection, for example—and three chapters putting forward applications where the model-based optimization brings a novel perspective. Developments in Model-Based Optimization and Control is a selection of contributions expanded and updated from the Optimisation-based Control and Estimation workshops held in November 2013 and November 2014. It forms a useful resource for academic researchers and graduate students interested in the state of the art in predictive control. Control engineers working in model-based optimization and control, particularly in its bioprocess applications will also find this collection instructive.
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spelling cern-21202102021-04-21T19:56:02Zdoi:10.1007/978-3-319-26687-9http://cds.cern.ch/record/2120210engOlaru, SorinGrancharova, AlexandraPereira, FernandoDevelopments in model-based optimization and control: distributed control and industrial applicationsEngineeringThis book deals with optimization methods as tools for decision making and control in the presence of model uncertainty. It is oriented to the use of these tools in engineering, specifically in automatic control design with all its components: analysis of dynamical systems, identification problems, and feedback control design. Developments in Model-Based Optimization and Control takes advantage of optimization-based formulations for such classical feedback design objectives as stability, performance and feasibility, afforded by the established body of results and methodologies constituting optimal control theory. It makes particular use of the popular formulation known as predictive control or receding-horizon optimization. The individual contributions in this volume are wide-ranging in subject matter but coordinated within a five-part structure covering material on: · complexity and structure in model predictive control (MPC); · collaborative MPC; · distributed MPC; · optimization-based analysis and design; and · applications to bioprocesses, multivehicle systems or energy management. The various contributions cover a subject spectrum including inverse optimality and more modern decentralized and cooperative formulations of receding-horizon optimal control. Readers will find fourteen chapters dedicated to optimization-based tools for robustness analysis, and decision-making in relation to feedback mechanisms—fault detection, for example—and three chapters putting forward applications where the model-based optimization brings a novel perspective. Developments in Model-Based Optimization and Control is a selection of contributions expanded and updated from the Optimisation-based Control and Estimation workshops held in November 2013 and November 2014. It forms a useful resource for academic researchers and graduate students interested in the state of the art in predictive control. Control engineers working in model-based optimization and control, particularly in its bioprocess applications will also find this collection instructive.Springeroai:cds.cern.ch:21202102015
spellingShingle Engineering
Olaru, Sorin
Grancharova, Alexandra
Pereira, Fernando
Developments in model-based optimization and control: distributed control and industrial applications
title Developments in model-based optimization and control: distributed control and industrial applications
title_full Developments in model-based optimization and control: distributed control and industrial applications
title_fullStr Developments in model-based optimization and control: distributed control and industrial applications
title_full_unstemmed Developments in model-based optimization and control: distributed control and industrial applications
title_short Developments in model-based optimization and control: distributed control and industrial applications
title_sort developments in model-based optimization and control: distributed control and industrial applications
topic Engineering
url https://dx.doi.org/10.1007/978-3-319-26687-9
http://cds.cern.ch/record/2120210
work_keys_str_mv AT olarusorin developmentsinmodelbasedoptimizationandcontroldistributedcontrolandindustrialapplications
AT grancharovaalexandra developmentsinmodelbasedoptimizationandcontroldistributedcontrolandindustrialapplications
AT pereirafernando developmentsinmodelbasedoptimizationandcontroldistributedcontrolandindustrialapplications