TY - JOUR

T1 - Cluster control of complex cyber-physical systems

AU - Uzhva, Denis

AU - Granichin, Oleg

N1 - Publisher Copyright: © 2021, Institute for Problems in Mechanical Engineering, Russian Academy of Sciences. All rights reserved.

PY - 2021/11/30

Y1 - 2021/11/30

N2 - To our minds, the real world appears as a composition of different interacting entitites, which demonstrate complex behavior. In the current paper, we primarly aim to study such networked systems by developing corresponding approaches to modeling them, given a class of tasks. We derive it from the primary concept of information and a system, with corresponding dynamics emerging from interactions between system components. As we progress through the study, we discover three pos-sible levels of certain synchronous pattern composition in complex systems: microscopic (the level of elemen-tary components), mesoscopic (the level of clusters), and macroscopic (the level of the whole system). Above all, we focus on the clusterization phenomenon, which allows to reduce system complexity by regarding only a small number of stable manifolds, corresponding to cluster synchronization of system component states—as op-posed to regarding the system as a whole or each elemen-tary component separately. Eventually, we demonstrate how an optimization problem for cluster control synthesis can be formulated for a simple discrete linear system with clusterization.

AB - To our minds, the real world appears as a composition of different interacting entitites, which demonstrate complex behavior. In the current paper, we primarly aim to study such networked systems by developing corresponding approaches to modeling them, given a class of tasks. We derive it from the primary concept of information and a system, with corresponding dynamics emerging from interactions between system components. As we progress through the study, we discover three pos-sible levels of certain synchronous pattern composition in complex systems: microscopic (the level of elemen-tary components), mesoscopic (the level of clusters), and macroscopic (the level of the whole system). Above all, we focus on the clusterization phenomenon, which allows to reduce system complexity by regarding only a small number of stable manifolds, corresponding to cluster synchronization of system component states—as op-posed to regarding the system as a whole or each elemen-tary component separately. Eventually, we demonstrate how an optimization problem for cluster control synthesis can be formulated for a simple discrete linear system with clusterization.

KW - Control of complex systems

KW - Discrete systems

KW - Multiagent technologies

UR - http://www.scopus.com/inward/record.url?scp=85120818514&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/5c9a159f-ee57-3ebb-82bd-5478ff69d728/

U2 - 10.35470/2226-4116-2021-10-3-191-200

DO - 10.35470/2226-4116-2021-10-3-191-200

M3 - Article

AN - SCOPUS:85120818514

VL - 10

SP - 191

EP - 200

JO - Cybernetics and Physics

JF - Cybernetics and Physics

SN - 2223-7038

IS - 3

ER -