923 research outputs found
Structural Target Controllability of Undirected Networks
In this paper, we study the target controllability problem of networked
dynamical systems, in which we are tasked to steer a subset of network states
towards a desired objective. More specifically, we derive necessary and
sufficient conditions for the structural target controllability problem of
linear time-invariant (LTI) systems with symmetric state matrices, such as
undirected dynamical networks with unknown link weights. To achieve our goal,
we first characterize the generic rank of symmetrically structured matrices, as
well as the modes of any numerical realization. Subsequently, we provide a
graph-theoretic necessary and sufficient condition for the structural
controllability of undirected networks with multiple control nodes. Finally, we
derive a graph-theoretic necessary and sufficient condition for structural
target controllability of undirected networks. Remarkably, apart from the
standard reachability condition, only local topological information is needed
for the verification of structural target controllability
Controllability of protein-protein interaction phosphorylation-based networks: Participation of the hub 14-3-3 protein family
Posttranslational regulation of protein function is an ubiquitous mechanism in eukaryotic cells. Here, we analyzed biological properties of nodes and edges of a human protein-protein interaction phosphorylation-based network, especially of those nodes critical for the network controllability. We found that the minimal number of critical nodes needed to control the whole network is 29%, which is considerably lower compared to other real networks. These critical nodes are more regulated by posttranslational modifications and contain more binding domains to these modifications than other kinds of nodes in the network, suggesting an intra-group fast regulation. Also, when we analyzed the edges characteristics that connect critical and non-critical nodes, we found that the former are enriched in domain-to-eukaryotic linear motif interactions, whereas the later are enriched in domain-domain interactions. Our findings suggest a possible structure for protein-protein interaction networks with a densely interconnected and self-regulated central core, composed of critical nodes with a high participation in the controllability of the full network, and less regulated peripheral nodes. Our study offers a deeper understanding of complex network control and bridges the controllability theorems for complex networks and biological protein-protein interaction phosphorylation-based networked systems.Fil: Uhart, Marina. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂa y EmbriologĂa de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂa y EmbriologĂa de Mendoza Dr. Mario H. Burgos; ArgentinaFil: Flores, Gabriel. Eventioz/eventbrite Company; ArgentinaFil: Bustos, Diego Martin. Consejo Nacional de Investigaciones CientĂficas y TĂ©cnicas. Centro CientĂfico TecnolĂłgico Conicet - Mendoza. Instituto de HistologĂa y EmbriologĂa de Mendoza Dr. Mario H. Burgos. Universidad Nacional de Cuyo. Facultad de Cienicas MĂ©dicas. Instituto de HistologĂa y EmbriologĂa de Mendoza Dr. Mario H. Burgos; Argentin
Control efficacy of complex networks
Acknowledgements W.-X.W. was supported by CNNSF under Grant No. 61573064, and No. 61074116 the Fundamental Research Funds for the Central Universities and Beijing Nova Programme, China. Y.-C.L. was supported by ARO under Grant W911NF-14-1-0504.Peer reviewedPublisher PD
Control energy of complex networks towards distinct mixture states
Controlling complex networked systems is a real-world puzzle that remains largely unsolved. Despite recent progress in understanding the structural characteristics of network control energy, target state and system dynamics have not been explored. We examine how varying the final state mixture affects the control energy of canonical and conformity-incorporated dynamical systems. We find that the control energy required to drive a network to an identical final state is lower than that required to arrive a non-identical final state. We also demonstrate that it is easier to achieve full control in a conformity-based dynamical network. Finally we determine the optimal control strategy in terms of the network hierarchical structure. Our work offers a realistic understanding of the control energy within the final state mixture and sheds light on controlling complex systems.This work was funded by The National Natural Science Foundation of China (Grant Nos. 61763013, 61703159, 61403421), The Natural Science Foundation of Jiangxi Province (No. 20171BAB212017), The Measurement and Control of Aircraft at Sea Laboratory (No. FOM2016OF010), and China Scholarship Council (201708360048). The Boston University Center for Polymer Studies is supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE-1213217, and by DTRA Grant HDTRA1-14-1-0017. (61763013 - National Natural Science Foundation of China; 61703159 - National Natural Science Foundation of China; 61403421 - National Natural Science Foundation of China; 20171BAB212017 - Natural Science Foundation of Jiangxi Province; FOM2016OF010 - Measurement and Control of Aircraft at Sea Laboratory; 201708360048 - China Scholarship Council; PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - DTRA)Published versio
Analytical controllability of deterministic scale-free networks and Cayley trees
According to the exact controllability theory, the controllability is
investigated analytically for two typical types of self-similar bipartite
networks, i.e., the classic deterministic scale-free networks and Cayley trees.
Due to their self-similarity, the analytical results of the exact
controllability are obtained, and the minimum sets of driver nodes (drivers)
are also identified by elementary transformations on adjacency matrices. For
these two types of undirected networks, no matter their links are unweighted or
(nonzero) weighted, the controllability of networks and the configuration of
drivers remain the same, showing a robustness to the link weights. These
results have implications for the control of real networked systems with
self-similarity.Comment: 7 pages, 4 figures, 1 table; revised manuscript; added discussion
about the general case of DSFN; added 3 reference
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