Overview
- Gives readers a series of novel insights into receding-horizon optimal control allowing them to keep abreast of developments across the whole area
- Provides information on various bioprocess-related applications
- Exemplifies novel optimization-based results in decentralized, distributed and cooperative control
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Control and Information Sciences (LNCIS, volume 464)
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Table of contents (17 chapters)
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Complexity and Structural Properties of Linear Model Predictive Control
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Distributed-coordinated and Multi-objective Features of Model Predictive Control
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Collaborative Model Predictive Control
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Applications of Optimization-Based Control and Identification
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Optimization-Based Analysis and Design for Particular Classes of Dynamical Systems
Keywords
- Bioprocesses
- Constrained Estimation
- Constrained and Predictive Control
- Control of Impulsive Systems
- Coordinated Control
- Distributed Predictive Control
- Fault-tolerant Control
- Model Predictive Control
- Multiagent Dynamical Systems
- Optimal Control
- Optimization-based Control
- Robustness in Constrained Control
- Set Invariance
- Unmanned Robotic Vehicle Systems
About this book
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.
Editors and Affiliations
About the editors
Alexandra Grancharova is Associate Professor at the University of Chemical Technology and Metallurgy (UCTM) in Sofia, Bulgaria. She has published two textbooks at UCTM (Model-based Control and Optimal and Robust Systems), which cover the material of identical M.Sc. courses at UCTM and one Springer monograph (A. Grancharova and T. A. Johansen, Explicit Nonlinear Model Predictive Control: Theory and Applications, Lecture Notes in Control and Information Sciences, vol.429). Beside that, Grancharova has published 9 book chapters, 18 articles in prestigious international journals and more than 60 peer-reviewed papers in the proceedings of international conferences. In 2000, she received the Bulgarian Academy of Sciences “Marin Drinov” award foryoung scientists. She is a member of the editorial board of the Automatics and Informatics journal (in Bulgarian), published by the John Atanasoff Society of Automatics and Informatics. Grancharova is a member of the IFAC Technical Committee on Control Design and an IPC member of several international conferences (Simultech 2011, 2012; IFAC NMPC 2012; Automatics and Informatics 2007 – 2014). She has been the coordinator of two international projects and has participated in several EU funded research projects (from 2000 to 2003 she held a postdoctoral position at the Department of Engineering Cybernetics at the Norwegian University of Science and Technology, Trondheim, Norway, under the EU Research Training Network - MAC).
Fernando Manuel Ferreira Lobo Pereira is Full Professor in Control and Automation at the Electrical and Computer Engineering Department, Faculty of Engineering of Porto University, and scientific coordinator of the SYSTEC Research Unit (ex- Institute for Systemsand Robotics – Porto where he led the Network Centric Control Systems group). He received the PhD in Control Theory from Imperial College of Science and Technology, London University, in 1986, and the Habilitation degree from Porto University in 1997. He is a member of IEEE, SIAM, APCA, AMS, INFORMS, SPM, and OE. His research work falls in the following areas: Control Theory (Non-smooth Analysis, Dynamic Optimization, Impulsive Control), Hybrid Systems, and Coordinated Control, and their application in the control of autonomous and/or networked systems arising mainly in unmanned vehicle systems. He has been involved in a large number of European and national research problems and has been expert adviser of EU to follow up funded research projects and evaluator of EU R&D proposals. He participated in ca 180 international technical scientific meetings, in the organization or the IPC of several international workshops, and many international conferences. He is in the editorial board of the journal Mathematical Problems in Engineering and has been regularly reviewing scientific and technical articles for conferences and journals such as Automatica, SIAM J. control and Optimization, IEEE J. Robotics & Autom., Systems and Control Letters, Math. of Industrial Systems, Annals of Operations Res., IEEE Robotics and Autom. Mag., Int. J. of Intelligent Control & Systems. Besides numerous technical reports he authored more than 250 scrutinized scientific and technical papers (of which 48 in journals) in reputed peer-reviewed international publications.
Bibliographic Information
Book Title: Developments in Model-Based Optimization and Control
Book Subtitle: Distributed Control and Industrial Applications
Editors: Sorin Olaru, Alexandra Grancharova, Fernando Lobo Pereira
Series Title: Lecture Notes in Control and Information Sciences
DOI: https://doi.org/10.1007/978-3-319-26687-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Softcover ISBN: 978-3-319-26685-5Published: 24 December 2015
eBook ISBN: 978-3-319-26687-9Published: 23 December 2015
Series ISSN: 0170-8643
Series E-ISSN: 1610-7411
Edition Number: 1
Number of Pages: XVIII, 381
Number of Illustrations: 84 b/w illustrations, 31 illustrations in colour
Topics: Control and Systems Theory, Calculus of Variations and Optimal Control; Optimization, Systems Theory, Control