A Caltech Library Service

System Level Synthesis via Dynamic Programming

Tseng, Shih-Hao and Amo Alonso, Carmen and Han, SooJean (2020) System Level Synthesis via Dynamic Programming. In: 2020 59th IEEE Conference on Decision and Control (CDC). IEEE , Piscataway, NJ, pp. 1718-1725. ISBN 9781728174471.

Full text is not posted in this repository. Consult Related URLs below.

Use this Persistent URL to link to this item:


System Level Synthesis (SLS) parametrization facilitates controller synthesis for large, complex, and distributed systems by incorporating system level constraints (SLCs) into a convex SLS problem and mapping its solution to stable controller design. Solving the SLS problem at scale efficiently is challenging, and current attempts take advantage of special system or controller structures to speed up the computation in parallel. However, those methods do not generalize as they rely on the specific system/controller properties. We argue that it is possible to solve general SLS problems more efficiently by exploiting the structure of SLS constraints. In particular, we derive dynamic programming (DP) algorithms to solve SLS problems. In addition to the plain SLS without any SLCs, we extend DP to tackle infinite horizon SLS approximation and entrywise linear constraints, which form a superclass of the locality constraints. Comparing to convex program solver and naive analytical derivation, DP solves SLS 4 to 12× faster and scales with little computation overhead. We also quantize the cost of synthesizing a controller that stabilizes the system in a finite horizon through simulations.

Item Type:Book Section
Related URLs:
URLURL TypeDescription
Tseng, Shih-Hao0000-0003-2376-9333
Amo Alonso, Carmen0000-0001-7593-5992
Additional Information:© 2020 IEEE.
Record Number:CaltechAUTHORS:20210121-152557719
Persistent URL:
Official Citation:S. -H. Tseng, C. A. Alonso and S. Han, "System Level Synthesis via Dynamic Programming," 2020 59th IEEE Conference on Decision and Control (CDC), Jeju Island, Korea (South), 2020, pp. 1718-1725, doi: 10.1109/CDC42340.2020.9304369
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107640
Deposited By: George Porter
Deposited On:22 Jan 2021 15:10
Last Modified:16 Nov 2021 19:04

Repository Staff Only: item control page