A quantitative framework for layered multirate control: Toward a theory of control architecture
Abstract
Complex engineered and natural control systems, such as those used in robotics, the power grid, human sensorimotor control, and the Internet, are characterized by needing to operate robustly and reliably across many spatiotemporal scales despite being implemented using highly constrained hardware and software. Remarkably, a universal design pattern centered aroundlayered control architectures(LCAs) has emerged to address these challenges across vastly different domains. These LCAs are the central object of study of this article (see “Summary”).
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In many modern cyber-physical systems, control is implemented in a networked architecture.
“In many modern cyber-physical systems, including cloud robotics, autonomous vehicle fleets, and teleoperated robots, control is implemented in a networked architecture [7]”
From Where to Put Safety? Control Barrier Function Placement in Networked Control Systems (2026) · cites this paper as [7]
Cites
Sterling, P., & Laughlin, S. (2015) · doi:10.7551/mitpress/9780262028707.001.0001 · Cited by 482 · cited 1× · see citing works
“These phenomena can indeed be observed in real visual systems [61].”
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Where to Put Safety? Control Barrier Function Placement in Networked Control Systems
Beger, S., Chen, Y., & Hirche, S. (2026) · IEEE Control Systems Letters · doi:10.1109/lcsys.2026.3710212
- Authors
- Matni, N., Ames, A. D., & Doyle, J. C.
- Affiliations
- University of Pennsylvania (US)
- University of St. Thomas - Minnesota (US)
- California Institute of Technology (US)
- Venue
- IEEE Control Systems
- Published
- 2024-06
- Volume
- 44
- Issue
- 3
- Pages
- 52-94
- ISSN
- 1066-033X (ISSN-L)
- 1941-000X
- OpenAlex
- W4399563158
- Cited by
- 39
- References
- 1
- Citations by year
- 2026: 12 · 2025: 23 · 2024: 4
- FWCI
- 6.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Control Systems (publishedVersion)
- Funders
- National Science Foundation (CPS-2038873, EECS-2231349, SLES-2331880)
- NSF CAREER (ECCS-2045834)
- NSF Award (CPS-1932091)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Systems Engineering Methodologies and Applications
- Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
- Keywords
- layered control architecture, multirate control, spatial and temporal scales, robustness, scalability, robot control, power system control, sensorimotor control, internet control
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