Parallel and distributed optimization methods for estimation and control in networks

System performance for networks composed of interconnected subsystems can be increased if the traditionally separated subsystems are jointly optimized. Recently, parallel and distributed optimization methods have emerged as a powerful tool for solving estimation and control problems in large-scale n...

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Veröffentlicht in:Journal of process control Jg. 21; H. 5; S. 756 - 766
Hauptverfasser: Necoara, Ion, Nedelcu, Valentin, Dumitrache, Ioan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.06.2011
Schlagworte:
Consensus
Convex optimization
Cooperative and distributed control
Duality theory
Estimation
Networks of interconnected subsystems
Parallel and distributed methods
Networks of interconnected subsystems
Parallel and distributed methods
Convex optimization
Estimation
Cooperative and distributed control
Duality theory
Consensus
ISSN:0959-1524, 1873-2771
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Beschreibung
Zusammenfassung:System performance for networks composed of interconnected subsystems can be increased if the traditionally separated subsystems are jointly optimized. Recently, parallel and distributed optimization methods have emerged as a powerful tool for solving estimation and control problems in large-scale networked systems. In this paper we review and analyze the optimization-theoretic concepts of parallel and distributed methods for solving coupled optimization problems and demonstrate how several estimation and control problems related to complex networked systems can be formulated in these settings. The paper presents a systematic framework for exploiting the potential of the decomposition structures as a way to obtain different parallel algorithms, each with a different tradeoff among convergence speed, message passing amount and distributed computation architecture. Several specific applications from estimation and process control are included to demonstrate the power of the approach.
ISSN:0959-1524
1873-2771
DOI:10.1016/j.jprocont.2010.12.010