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On Fundamental Limitations of Dynamic Feedback Control in Regular Large-Scale Networks
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0001-8975-1801
Cold Spring Harbor Lab, Cold Spring Harbor, NY 11724 USA..
KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).ORCID iD: 0000-0003-1835-2963
Univ Calif Santa Barbara, Dept Mech Engn, Santa Barbara, CA 93106 USA..
2019 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 12, p. 4936-4951Article in journal (Refereed) Published
Abstract [en]

In this paper, we study fundamental performance limitations of distributed feedback control in large-scale networked dynamical systems. Specifically, we address the question of whether dynamic feedback controllers perform better than static (memoryless) ones when subject to locality constraints. We consider distributed linear consensus and vehicular formation control problems modeled over toric lattice networks. For the resulting spatially invariant systems, we study the large-scale asymptotics (in network size) of global performance metrics that quantify the level of network coherence. With static feedback from relative state measurements, such metrics are known to scale unfavorably in lattices of low spatial dimensions, preventing, for example, a one-dimensional string of vehicles to move like a rigid object. We show that the same limitations in general apply also to dynamic feedback control that is locally of first order. This means that the addition of one local state to the controller gives a similar asymptotic performance to the memoryless case. This holds unless the controller can access noiseless measurements of its local state with respect to an absolute reference frame, in which case the addition of controller memory may fundamentally improve performance. In simulations of platoons with 20-200 vehicles, we show that the performance limitations we derive manifest as unwanted accordionlike motions. Similar behaviors are to be expected in any network that is embeddable in a low-dimensional toric lattice, and the same fundamental limitations would apply. To derive our results, we present a general technical framework for the analysis of stability and performance of spatially invariant systems in the limit of large networks.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 64, no 12, p. 4936-4951
Keywords [en]
Vehicle dynamics, Lattices, Feedback control, Measurement, Power system dynamics, Control systems, Protocols, Networked control systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-268964DOI: 10.1109/TAC.2019.2909811ISI: 000502278300007Scopus ID: 2-s2.0-85068842657OAI: oai:DiVA.org:kth-268964DiVA, id: diva2:1397942
Note

QC 20200227

Available from: 2020-02-27 Created: 2020-02-27 Last updated: 2020-04-02Bibliographically approved

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Tegling, Emma

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