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Reduction of the small gain condition for large‐scale interconnections
Author(s) -
Dashkovskiy S.,
Kosmykov M.
Publication year - 2015
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.3111
Subject(s) - interconnection , computation , computer science , heuristic , reduction (mathematics) , lyapunov function , stability (learning theory) , high gain antenna , control theory (sociology) , automatic gain control , function (biology) , topology (electrical circuits) , mathematics , algorithm , control (management) , nonlinear system , computer network , engineering , artificial intelligence , bandwidth (computing) , amplifier , physics , geometry , quantum mechanics , machine learning , combinatorics , electrical engineering , evolutionary biology , biology
Summary The small gain condition is sufficient for input‐to‐state stability (ISS) of interconnected systems. However, verification of the small gain condition requires large amount of computations in the case of a large size of the system. To facilitate this procedure, we aggregate the subsystems and the gains between the subsystems that belong to certain interconnection patterns (motifs) by using three heuristic rules. These rules are based on three motifs: sequentially connected nodes, nodes connected in parallel, and almost disconnected subgraphs. Aggregation of these motifs keeps the structure of the mutual influences between the subsystems in the network. Furthermore, fulfillment of the reduced small gain condition implies ISS of the large network. Thus, such reduction allows to decrease the number of computations needed to verify the small gain condition. Finally, an ISS‐Lyapunov function for the large network can be constructed using the reduced small gain condition. Applications of these rules is illustrated on an example. Copyright © 2013 John Wiley & Sons, Ltd.