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Complexity of spatially interconnected systems
Citation Link: https://doi.org/10.15480/882.1336
Publikationstyp
Doctoral Thesis
Date Issued
2016-11
Sprache
English
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2016-10-25
Institut
TORE-DOI
First published in
Mathematik;
Publisher Link
Publisher
Verlag Dr. Hut
In contrast to lumped-parameter systems which are defined with respect to the temporal variable only, spatially interconnected (distributed-parameter) systems are defined with respect to temporal as well as spatial variables. Spatially interconnected systems are represented as a spatial-interconnection of subsystems. In practice the resulting complexity often renders the associated analysis and synthesis problems intractable. Therefore, constructing reduced complexity models without losing the characteristic features of the original model is practical. The spatial interconnection structure of the system should be preserved in the reduced model as well. Spatially interconnected systems can be distinguished into temporal- and spatial-invariant (parameter-invariant) systems, and temporal- and spatial-varying (parameter-varying) systems. A main feature of spatially interconnected systems is that they are causal with respect to time (temporal variable), but non-causal with respect to space (spatial variable). This thesis provides methods for solving the reduction problem for both parameter-invariant and parameter-varying systems, respectively, where different kinds of complexity for such systems are considered. In addition, error bounds are proved. The proposed methods take into account the non-causality of the system. Theoretical results are illustrated on an experimentally identified model of an actuated beam.
Subjects
Spatially Interconnected Systems
Model Order Reduction
DDC Class
620: Ingenieurwissenschaften
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