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Scalable system level synthesis for virtually localizable systems

Matni, Nikolai and Wang, Yuh-Shyang and Anderson, James (2017) Scalable system level synthesis for virtually localizable systems. In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 3473-3480. ISBN 978-1-5090-2874-0. http://resolver.caltech.edu/CaltechAUTHORS:20180126-083714820

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Abstract

In previous work, we developed the system level approach to controller synthesis, and showed that under suitable assumptions, this framework allowed for the synthesis of localized controllers. We further showed that such localized controllers enjoy O(1) synthesis and implementation complexity relative to the dimension of the global system, making them particularly well suited for the control of large-scale cyber-physical systems. However, the assumptions under which a system is localizable are stringent: roughly, a system is localizable if the controller has the necessary actuation, sensing and communication resources to “get out ahead” of the propagation of a disturbance and neutralize it, thus containing its effect to a localized spatiotemporal region. In this paper, we relax the assumption of exact localizability, and develop a controller synthesis methodology that is applicable to arbitrary systems that are in an appropriate sense “easy to control.” We focus on the state-feedback setting and develop a simple necessary and sufficient condition for robust stability using the system level approach. We then leverage this condition, along with the introduction of virtual actuation, communication and system responses into the synthesis process, to design stabilizing controllers that have (i) O(1) synthesis and implementation complexity and (ii) guaranteed performance bounds. We end with a power-inspired example demonstrating the usefulness of these techniques, wherein we synthesize a near globally optimal controller for a system that is neither localizable nor quadratically invariant.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/CDC.2017.8264168DOIArticle
http://ieeexplore.ieee.org/document/8264168/PublisherArticle
ORCID:
AuthorORCID
Matni, Nikolai0000-0003-4936-3921
Wang, Yuh-Shyang0000-0001-7357-7247
Additional Information:© 2017 IEEE. Date Added to IEEE Xplore: 23 January 2018. This research was supported by grants from the AFOSR and NSF, and by gifts from Huawei and Google.
Funders:
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)UNSPECIFIED
NSFUNSPECIFIED
HuaweiUNSPECIFIED
GoogleUNSPECIFIED
Record Number:CaltechAUTHORS:20180126-083714820
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20180126-083714820
Official Citation:N. Matni, Y. S. Wang and J. Anderson, "Scalable system level synthesis for virtually localizable systems," 2017 IEEE 56th Annual Conference on Decision and Control (CDC), Melbourne, Australia, 2017, pp. 3473-3480. doi: 10.1109/CDC.2017.8264168
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84541
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:31 Jan 2018 00:44
Last Modified:31 Jan 2018 00:44

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