The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Control Barrier Function Based Quadratic Programs for Safety Critical Systems
Open accessAbstract
Safety critical systems involve the tight coupling between potentially conflicting control objectives and safety constraints. As a means of creating a formal framework for controlling systems of this form, and with a view toward automotive applications, this paper develops a methodology that allows safety conditions-expressed as control barrier functions-to be unified with performance objectives-expressed as control Lyapunov functions-in the context of real-time optimization-based controllers. Safety conditions are specified in terms of forward invariance of a set, and are verified via two novel generalizations of barrier functions; in each case, the existence of a barrier function satisfying Lyapunov-like conditions implies forward invariance of the set, and the relationship between these two classes of barrier functions is characterized. In addition, each of these formulations yields a notion of control barrier function (CBF), providing 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 achievement of control objectives (represented by CLFs) subject to conditions on the admissible states of the system (represented by CBFs). The mediation of safety and performance through a QP is demonstrated on adaptive cruise control and lane keeping, two automotive control problems that present both safety and performance considerations coupled with actuator bounds.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Cited by
Cheng, R., Orosz, G., Murray, R. M., & Burdick, J. W. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33013387 · Cited by 611
“The existence of a CBF implies that there exists a deterministic controller u CBF : S → A such that the set C is forward invariant for system (1) (Agrawal and Sreenath 2017; Ames et al. 2017).”
BackgroundInput-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
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
Self-citationWabersich, K. P., Taylor, A. J., Choi, J. J., Sreenath, K., Tomlin, C. J., Ames, A. D., & Zeilinger, M. N. (2023) · IEEE Control Systems · doi:10.1109/mcs.2023.3291885 · Cited by 132
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Metadata
- Authors
- Ames, A. D., Xu, X., Grizzle, J. W., & Tabuada, P.
- Venue
- IEEE Transactions on Automatic Control
- Published
- 2017-08
- Volume
- 62
- Issue
- 8
- Pages
- 3861-3876
- ISSN
- 0018-9286 (ISSN-L)
- 1558-2523
- OpenAlex
- W2560504659
- Cited by
- 2,512
- References
- 1
- FWCI
- 32.27
- Type
- journal article
- Language
- en
- Open access
- green
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