Pasqualetti, F., Favaretto, C., Zhao, S. orcid.org/0000-0003-3098-8059 et al. (1 more author) (2018) Fragility and controllability tradeoff in complex networks. In: Proceedings of the American Control Conference. 2018 Annual American Control Conference, 27-29 Jun 2018, Milwaukee, WI, USA. IEEE , pp. 216-221. ISBN 9781538654286
Abstract
© 2018 AACC. Mathematical theories and empirical evidence suggest that several complex natural and man-made systems are fragile: as their size increases, arbitrarily small and localized alterations of the system parameters may trigger system-wide failures. Examples are abundant, from perturbation of the population densities leading to extinction of species in ecological networks [1], to structural changes in metabolic networks preventing reactions [2], cascading failures in power networks [3], and the onset of epileptic seizures following alterations of structural connectivity among populations of neurons [4]. While fragility of these systems has long been recognized [5], convincing theories of why natural evolution or technological advance has failed, or avoided, to enhance robustness in complex systems are still lacking. In this paper we propose a mechanistic explanation of this phenomenon. We show that a fundamental tradeoff exists between fragility of a complex network and its controllability degree, that is, the control energy needed to drive the network state to a desirable state. We provide analytical and numerical evidence that easily controllable networks are fragile, suggesting that natural and man-made systems can either be resilient to parameters perturbation or efficient to adapt their state in response to external excitations and controls.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Controllability; Eigenvalues and eigenfunctions; Perturbation methods; Complex networks; Robustness; Sociology; Statistics |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 05 Nov 2018 16:43 |
Last Modified: | 05 Nov 2018 16:43 |
Published Version: | https://doi.org/10.23919/ACC.2018.8431836 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.23919/ACC.2018.8431836 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138232 |