Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published September 2017 | public
Journal Article Open

Thinking Fast and Slow: Optimization Decomposition Across Timescales

Abstract

Many real-world control systems, such as the smart grid and software defined networks, have decentralized components that react quickly using local information and centralized components that react slowly using a more global view. This work seeks to provide a theoretical framework for how to design controllers that are decomposed across timescales in this way. The framework is analogous to how the network utility maximization framework uses optimization decomposition to distribute a global control problem across independent controllers, each of which solves a local problem; except our goal is to decompose a global problem temporally, extracting a timescale separation. Our results highlight that decomposition of a multi-timescale controller into a fast timescale, reactive controller and a slow timescale, predictive controller can be near-optimal in a strong sense. In particular, we exhibit such a design, named Multi-timescale Reflexive Predictive Control (MRPC), which maintains a per-timestep cost within a constant factor of the offline optimal in an adversarial setting.

Additional Information

Copyright is held by author/owner(s).

Attached Files

Submitted - 1704.07785.pdf

Files

1704.07785.pdf
Files (186.0 kB)
Name Size Download all
md5:d4c5399d500b475a7ed3936b82e5e3d0
186.0 kB Preview Download

Additional details

Created:
August 19, 2023
Modified:
August 19, 2023