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Localized LQG Optimal Control for Large-Scale Systems

Wang, Yuh-Shyang and Matni, Nikolai (2016) Localized LQG Optimal Control for Large-Scale Systems. In: 2016 American Control Conference (ACC). IEEE , Piscataway, NJ, pp. 1954-1961. ISBN 978-1-4673-8680-7 .

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This paper poses and solves the localized linear quadratic Gaussian (LLQG) optimal control problem. In particular, we show that for large-scale localizable systems, that is to say systems for which the closed loop effect of each disturbance can be contained to within a local neighborhood despite communication delays between sub-controllers, the synthesis and implementation of a LLQG optimal controller can be performed in a scalable way. We combine our prior results on the state-feedback version of this problem with the alternating direction method of multipliers (ADMM) algorithm to formulate a synthesis algorithm that can be solved in a distributed fashion, with each subsystem solving a problem of constant dimension independent of the global problem size. The result is a controller synthesis and implementation scheme that can scale to systems of arbitrary dimension, subject to certain conditions on the communication, actuation and sensing schemes holding. Simulations show that for some systems, the LLQG optimal controller can achieve transient performance similar to that of a centralized H2 optimal controller. We also demonstrate our algorithm on a system with about 104 states composed of heterogeneous and dynamically coupled subsystems - here the distributed and centralized optimal controllers cannot be computed.

Item Type:Book Section
Related URLs:
URLURL TypeDescription
Wang, Yuh-Shyang0000-0001-7357-7247
Matni, Nikolai0000-0003-4936-3921
Additional Information:© 2016 AACC. This research was in part supported by NSF NetSE, AFOSR, the Institute for Collaborative Biotechnologies through grant W911NF-09-0001 from the U.S. Army Research Office, and from MURIs “Scalable, Data-Driven, and Provably-Correct Analysis of Networks” (ONR) and “Tools for the Analysis and Design of Complex Multi-Scale Networks” (ARO). The content does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)UNSPECIFIED
Army Research Office (ARO)W911NF-09-0001
Office of Naval Research (ONR)UNSPECIFIED
Record Number:CaltechAUTHORS:20160802-082120659
Persistent URL:
Official Citation:Y. S. Wang and N. Matni, "Localized LQG optimal control for large-scale systems," 2016 American Control Conference (ACC), Boston, MA, USA, 2016, pp. 1954-1961. doi: 10.1109/ACC.2016.7525205
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:69377
Deposited By: Ruth Sustaita
Deposited On:02 Aug 2016 23:34
Last Modified:03 Oct 2019 10:21

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