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Thinking Fast and Slow: Optimization Decomposition Across Timescales. (arXiv:1704.07785v1 [math.OC])
来源于:arXiv
Many real-world control systems, such as the smart grid and human
sensorimotor control systems, have decentralized components that react quickly
using local information and centralized components that react slowly using a
more global view. This paper 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 maintain 查看全文>>