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Control barrier function based quadratic programs with application to adaptive cruise control
Abstract
This paper develops a control methodology that unifies control barrier functions and control Lyapunov functions through quadratic programs. The result is demonstrated on adaptive cruise control, which presents both safety and performance considerations, as well as actuator bounds. We begin by presenting a novel notion of a barrier function associated with a set, formulated in the context of Lyapunov-like conditions; the existence of a barrier function satisfying these conditions implies forward invariance of the set. This formulation naturally yields a notion of control barrier function (CBF), yielding inequality constraints in the control input that, when satisfied, again imply forward invariance of the set. Through these constructions, CBFs can naturally be unified with control Lyapunov functions (CLFs) in the context of a quadratic program (QP); this allows for the simultaneous achievement of control objectives (represented by CLFs) subject to conditions on the admissible states of the system (represented by CBFs). These formulations are illustrated in the context of adaptive cruise control, where the control objective of achieving a desired speed is balanced by the minimum following conditions on a lead car and force-based constraints on acceleration and braking.
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Citations
Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Cited by
Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function
Zeng, J., Zhang, B., & Sreenath, K. (2021) · 2021 American Control Conference (ACC) · doi:10.23919/acc50511.2021.9483029 · Cited by 390
Input-to-State Safety With Control Barrier Functions
Kolathaya, S., & Ames, A. D. (2019) · IEEE Control Systems Letters · doi:10.1109/lcsys.2018.2853698 · Cited by 328
Self-citationControl Barrier Functions for Signal Temporal Logic Tasks
Lindemann, L., & Dimarogonas, D. V. (2019) · IEEE Control Systems Letters · doi:10.1109/lcsys.2018.2853182 · Cited by 319
Nonsmooth Barrier Functions With Applications to Multi-Robot Systems
Glotfelter, P., Cortes, J., & Egerstedt, M. (2017) · IEEE Control Systems Letters · doi:10.1109/lcsys.2017.2710943 · Cited by 312
Singletary, A., Klingebiel, K., Bourne, J., Browning, A., Tokumaru, P., & Ames, A. (2021) · 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636670 · Cited by 182
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Metadata
- Authors
- Ames, A. D., Grizzle, J. W., & Tabuada, P.
- Venue
- 53rd IEEE Conference on Decision and Control
- Publisher
- IEEE
- Published
- 2014-12
- Pages
- 6271-6278
- ISSN
- 0191-2216 (ISSN-L)
- OpenAlex
- W1980569135
- Cited by
- 974
- References
- 1
- FWCI
- 27.78
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Ames, A. D., Grizzle, J. W., & Tabuada, P. (2014). Control barrier function based quadratic programs with application to adaptive cruise control. 53rd IEEE Conference on Decision and Control. https://doi.org/10.1109/cdc.2014.7040372
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
