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Cited by 65Advanced Control Systems OptimizationFormal Methods in VerificationAdaptive Control of Nonlinear Systems

Multi-Rate Control Design Leveraging Control Barrier Functions and Model Predictive Control Policies

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Rosolia, Ugo, Ames, Aaron D.·2021·IEEE Control Systems Letters
DOI 10.1109/lcsys.2020.3008326
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Abstract

In this letter we present a multi-rate control architecture for safety critical systems. We consider a high level planner and a low level controller which operate at different frequencies. This multi-rate behavior is described by a piecewise nonlinear model which evolves on a continuous and a discrete level. First, we present sufficient conditions which guarantee recursive constraint satisfaction for the closed-loop system. Afterwards, we propose a control design methodology which leverages Control Barrier Functions (CBFs) for low level control and Model Predictive Control (MPC) policies for high level planning. The control barrier function is designed using the full nonlinear dynamical model and the MPC is based on a simplified planning model. When the nonlinear system is control affine and the high level planning model is linear, the control actions are computed by solving convex optimization problems at each level of the hierarchy. Finally, we show the effectiveness of the proposed strategy on a simulation example, where the low level control action is updated at a higher frequency than the high level command.

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  • The architectural implications of enforcing safety locally or remotely have not yet been systematically analyzed.

    “While recent work has considered potential architectures for CBF in networked [9] or multi-rate [10] setups, the architectural implications of enforcing safety locally or remotely have not yet been systematically analyzed.”

    From Where to Put Safety? Control Barrier Function Placement in Networked Control Systems (2026) · cites this paper as [10]

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Research works printed but not linked: 21

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Cited by

Sorted by citations

Authors
Rosolia, U., & Ames, A. D.
Affiliations
California Institute of Technology (US)
ORCID
Venue
IEEE Control Systems Letters
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2021-07
Volume
5
Issue
3
Pages
1007-1012
ISSN
2475-1456 (ISSN-L)
DOI
10.1109/lcsys.2020.3008326
OpenAlex
W3014836776
Cited by
65
References
0
Citations by year
2026: 7 · 2025: 11 · 2024: 17 · 2023: 12 · 2022: 7 · 2021: 11
FWCI
3.71
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Control Systems Letters (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • CaltechAUTHORS (California Institute of Technology) (submittedVersion)
  • arXiv (Cornell University)
Funders
National Science Foundation (1932091)
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Optimization
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Formal Methods in Verification
  • Physical Sciences › Engineering › Control and Systems Engineering › Adaptive Control of Nonlinear Systems
Keywords
multirate control, control barrier functions, model predictive control, hierarchical control, safety-critical systems, high-level planning, low-level control, convex optimization, control-affine systems

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