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System level parameterizations, constraints and synthesis

Wang, Yuh-Shyang and Matni, Nikolai and Doyle, John C. (2017) System level parameterizations, constraints and synthesis. In: 2017 American Control Conference. IEEE , Piscataway, NJ. (In Press) http://resolver.caltech.edu/CaltechAUTHORS:20170531-104451494

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Abstract

We introduce the system level approach to controller synthesis, which is composed of three elements: System Level Parameterizations (SLPs), System Level Constraints (SLCs) and System Level Synthesis (SLS) problems. SLPs provide a novel parameterization of all internally stabilizing controllers and the system responses that they achieve. These can be combined with SLCs to provide parameterizations of constrained stabilizing controllers. We provide a catalog of useful SLCs, and show that by using SLPs with SLCs, we can parameterize the largest known class of constrained stabilizing controllers that admit a convex characterization. Finally, we formulate the SLS problem, and show that it defines the broadest known class of constrained optimal control problems that can be solved using convex programming. We end by using the system level approach to computationally explore tradeoffs in controller performance, architecture cost, robustness and synthesis/implementation complexity.


Item Type:Book Section
Additional Information:© IEEE 2017. Thanks to funding from AFOSR and NSF and gifts from Huawei and Google.
Funders:
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)UNSPECIFIED
NSFUNSPECIFIED
Subject Keywords:Optimal control, Distributed control, Control system architecture
Record Number:CaltechAUTHORS:20170531-104451494
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170531-104451494
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:77854
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:31 May 2017 17:50
Last Modified:31 May 2017 20:59

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