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System Level Synthesis with State and Input Constraints

Chen, Yuxiao and Anderson, James (2019) System Level Synthesis with State and Input Constraints. In: 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 5258-5263. ISBN 9781728113982.

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This paper addresses the problem of designing distributed controllers with state and input constraints in the System Level Synthesis (SLS) framework. Using robust optimization, we show how state and actuation constraints can be incorporated into the SLS structure. Moreover, we show that the dual variable associated with the constraint has the same sparsity pattern as the SLS parametrization, and therefore the computation distributes using a simple primal-dual algorithm. We provide a stability analysis for SLS design with input saturation under the Internal Model Control (IMC) framework. We show that the closed-loop system with saturation is stable if the controller has a gain less than one. In addition, a saturation compensation scheme that incorporates the saturation information is proposed which improves the naive SLS design under saturation.

Item Type:Book Section
Related URLs:
URLURL TypeDescription Paper
Chen, Yuxiao0000-0001-5276-7156
Anderson, James0000-0001-8210-6527
Additional Information:© 2019 IEEE. We gratefully acknowledge John C. Doyle for suggesting we look at internal model control theory in connection with this problem.
Record Number:CaltechAUTHORS:20200911-133139643
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Official Citation:Y. Chen and J. Anderson, "System Level Synthesis with State and Input Constraints," 2019 IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019, pp. 5258-5263, doi: 10.1109/CDC40024.2019.9029745
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105359
Deposited By: George Porter
Deposited On:11 Sep 2020 21:40
Last Modified:19 Jan 2023 20:11

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