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Frontiers in Scalable Distributed Control: SLS, MPC, and Beyond

Li, Jing Shuang and Amo Alonso, Carmen and Doyle, John C. (2021) Frontiers in Scalable Distributed Control: SLS, MPC, and Beyond. In: 2021 American Control Conference (ACC). IEEE , Piscataway, NJ, pp. 2720-2725. ISBN 978-1-6654-4197-1.

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The System Level Synthesis (SLS) approach facilitates distributed control of large cyberphysical networks in an easy-to-understand, computationally scalable way. We present an overview of the SLS approach and its associated extensions in nonlinear control, MPC, adaptive control, and learning for control. To illustrate the effectiveness of SLS-based methods, we present a case study motivated by the power grid, with communication constraints, actuator saturation, disturbances, and changing setpoints. This simple but challenging case study necessitates the use of model predictive control (MPC); however, standard MPC techniques often scales poorly to large systems and incurs heavy computational burden. To address this challenge, we combine two SLS-based controllers to form a layered MPC-like controller. Our controller has constant computational complexity with respect to the system size, gives a 20-fold reduction in online computation requirements, and still achieves performance that is within 3% of the centralized MPC controller.

Item Type:Book Section
Related URLs:
URLURL TypeDescription Paper
Li, Jing Shuang0000-0003-4931-8709
Amo Alonso, Carmen0000-0001-7593-5992
Doyle, John C.0000-0002-1828-2486
Alternate Title:MPC Without the Computational Pain: The Benefits of SLS and Layering in Distributed Control
Additional Information:© 2021 AACC.
Record Number:CaltechAUTHORS:20210510-141354333
Persistent URL:
Official Citation:J. S. Li, C. A. Alonso and J. C. Doyle, "Frontiers in Scalable Distributed Control: SLS, MPC, and Beyond," 2021 American Control Conference (ACC), 2021, pp. 2720-2725, doi: 10.23919/ACC50511.2021.9483130
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109058
Deposited By: George Porter
Deposited On:10 May 2021 21:50
Last Modified:25 Aug 2021 17:26

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