System level parameterizations, constraints and synthesis
- Creators
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Wang, Yuh-Shyang
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Matni, Nikolai
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Doyle, John C.
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.
Additional Information
© 2017 IEEE. Thanks to funding from AFOSR and NSF and gifts from Huawei and Google.Attached Files
Submitted - system_level_acc17.pdf
Files
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Additional details
- Eprint ID
- 77854
- Resolver ID
- CaltechAUTHORS:20170531-104451494
- Air Force Office of Scientific Research (AFOSR)
- NSF
- Huawei
- Created
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2017-05-31Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field