Distributed Model Predictive Control Made Easy

Inbunden, Engelska, 2013

Av José M. Maestre, Rudy R. Negenborn, Jose M. Maestre

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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.

Produktinformation

Utgivningsdatum2013-11-25
Mått155 x 235 x 38 mm
Vikt1 034 g
FormatInbunden
SpråkEngelska
SerieIntelligent Systems, Control and Automation: Science and Engineering
Antal sidor600
FörlagSpringer
ISBN9789400770058

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Preface.- List of Contributors.- On 35 Approaches for Distributed MPC Made Easy, by R.R. Negenborn, J.M. Maestre.- Part I: From Small-Scale to Large-Scale. The Group of Autonomous Systems Perspective.- 1 Bargaining game based distributed MPC, by F. Valencia, J.D. López, J.A. Patiño, J.J. Espinosa.- 2 Cooperative tube-based distributed MPC for linear uncertain systems coupled via constraints, by P.A. Trodden, A.G. Richards.- 3 Price-driven coordination for distributed NMPC using a feedback control law, by R. Martí, D. Sarabia, C. de Prada.- 4 Distributed MPC for consensus and synchronization, by M.A. Müller, F. Allgöwer.- 5 Distributed MPC under coupled constraints based on Dantzig-Wolfe decomposition, by R. Bourdais, J. Buisson, D. Dumur, H. Guéguen, P-D. Moroşan.- 6 Distributed MPC via dual decomposition and alternative direction method of multipliers , by F. Farokhi, I. Shames, K.H. Johansson.- 7 D-SIORHC, distributed MPC with stability constraints based on a game approach, by J.M. Lemos, J.M. Igreja.- 8 A distributed-in-time NMPC-based coordination mechanism for resource sharing problems , by M.Y. Lamoudi, M. Alamir, P. Béguery.- 9 Rate analysis of inexact dual fast gradient method for distributed MPC, by I. Necoara.- 10 Distributed MPC via dual decomposition , by B. Biegel, J. Stoustrup, P. Andersen.- 11 Distributed optimization for MPC of linear dynamic networks, by E. Camponogara.- 12 Adaptive quasi-decentralized MPC of networked process systems, by Y. Hu, N.H. El-Farra.- 13 Distributed Lyapunov-based MPC, by R. Hermans, M. Lazar, A. Jokić.- 14 A distributed reference management scheme in presence of non-convex constraints: an MPC based approach, by F. Tedesco, D.M. Raimondo, A. Casavola.- 15 The distributed command governor approach in a nutshell, by A. Casavola, E. Garone, F. Tedesco.- 16 Mixed-integer programming techniques in distributed MPC problems, by I. Prodan, F. Stoican, S. Olaru, C. Stoica, S-I. Niculescu.- 17 Distributed MPCof interconnected nonlinear systems by dynamic dual decomposition, by A. Grancharova, T.A. Johansen.- 18 Generalized accelerated gradient methods for distributed MPC based on dual decomposition, by P. Giselsson, A. Rantzer.- 19 Distributed multiple shooting for large scale nonlinear systems, by A. Kozma, C. Savorgnan, M. Diehl.- 20 Nash-based distributed MPC for multi-rate systems , by S. Roshany-Yamchi, R.R. Negenborn, A.A. Cornelio.- Part II: From Large-Scale to Small-Scale. The Decomposed Monolithic System Perspective.- 21 Cooperative dynamic MPC for networked control systems, by I. Jurado, D.E. Quevedo, K.H. Johansson, A. Ahlén.- 22 Parallel implementation of hybrid MPC, by D. Axehill, A. Hansson.- 23 A hierarchical MPC approach with guaranteed feasibility for dynamically coupled linear systems, by M.D. Doan, T. Keviczky, B. De Schutter.- 24 Distributed MPC based on a team game, by J.M. Maestre, F.J. Muros, F. Fele, D. Muñoz de la Peña, E. F. Camacho.- 25 Distributed MPC: A noncooperative approach based on robustness concepts , by G. Betti, M. Farina, R. Scattolini.- 26 Decompositions of augmented Lagrange formulations for serial and parallel distributed MPC, by R.R. Negenborn.- 27 A hierarchical distributed MPC approach: A practical implementation, by A. Zafra-Cabeza, J.M. Maestre.- 28 Distributed MPC based on agent negotiation, by J.M. Maestre, D. Muñoz de la Peña, E.F. Camacho.- 29 Lyapunov-based distributed MPC schemes: Sequential and iterative approaches, by J. Liu, D. Muñoz de la Peña, P.D. Christofides.- 30 Multi-layer decentralized MPC of large-scale networked systems, by C. Ocampo-Martinez, V. Puig, J.M. Grosso, S. Montes-de-Oca.- 31 Distributed MPC using reinforcement learning based negotiation: Application to large scale systems, by B. Morcego, V. Javalera, V. Puig, R. Vito.- 32 Hierarchical MPC for multiple commodity transportation networks, by J.L. Nabais, R.R. Negenborn, R.B. Carmona-Benítez, L.F. Mendonça, M.A. Botto.- 33 On the useof suboptimal solvers for efficient cooperative distributed linear MPC, by G. Pannocchia, S.J. Wright, J.B. Rawlings.- 34 Cooperative distributed MPC integrating a steady state target optimizer, by A. Ferramosca, D. Limon, A.H. González.- 35 Cooperative MPC with guaranteed exponential stability, by A. Ferramosca.

From the reviews: "This book presents a modern solution for the control and monitoring of complex structures using distributed control systems based on high-level communication protocols dedicated to control applications. ... this book will be particularly interesting to readers in academia and research who wish to acquire a theoretical knowledge base and identify new areas of research. ... practitioners may find it a useful handbook to assist in current projects." (Eugen Petac, Computing Reviews, February, 2014)