A Survey on the Control Lyapunov Function and Control Barrier Function for Nonlinear-Affine Control Systems

Li, B; Wen, S; Yan, Z; Wen, G; Huang, T

A Survey on the Control Lyapunov Function and Control Barrier Function for Nonlinear-Affine Control Systems

Li, B

Wen, S

Yan, Z

Wen, G Huang, T

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE/CAA Journal of Automatica Sinica, 2023, 10, (3), pp. 584-602
Issue Date:: 2023-03-01

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Field	Value	Language
dc.contributor.author	Li, B https://orcid.org/0000-0002-6310-1533
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Yan, Z https://orcid.org/0000-0003-3368-2100
dc.contributor.author	Wen, G
dc.contributor.author	Huang, T
dc.date.accessioned	2024-01-16T21:32:32Z
dc.date.available	2024-01-16T21:32:32Z
dc.date.issued	2023-03-01
dc.identifier.citation	IEEE/CAA Journal of Automatica Sinica, 2023, 10, (3), pp. 584-602
dc.identifier.issn	2329-9266
dc.identifier.issn	2329-9274
dc.identifier.uri	http://hdl.handle.net/10453/174650
dc.description.abstract	This survey provides a brief overview on the control Lyapunov function (CLF) and control barrier function (CBF) for general nonlinear-affine control systems. The problem of control is formulated as an optimization problem where the optimal control policy is derived by solving a constrained quadratic programming (QP) problem. The CLF and CBF respectively characterize the stability objective and the safety objective for the nonlinear control systems. These objectives imply important properties including controllability, convergence, and robustness of control problems. Under this framework, optimal control corresponds to the minimal solution to a constrained QP problem. When uncertainties are explicitly considered, the setting of the CLF and CBF is proposed to study the input-to-state stability and input-to-state safety and to analyze the effect of disturbances. The recent theoretic progress and novel applications of CLF and CBF are systematically reviewed and discussed in this paper. Finally, we provide research directions that are significant for the advance of knowledge in this area.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE/CAA Journal of Automatica Sinica
dc.relation.isbasedon	10.1109/JAS.2023.123075
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	4007 Control engineering, mechatronics and robotics
dc.title	A Survey on the Control Lyapunov Function and Control Barrier Function for Nonlinear-Affine Control Systems
dc.type	Journal Article
utslib.citation.volume	10
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2024-01-16T21:32:31Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	10
utslib.citation.issue	3

Abstract:

This survey provides a brief overview on the control Lyapunov function (CLF) and control barrier function (CBF) for general nonlinear-affine control systems. The problem of control is formulated as an optimization problem where the optimal control policy is derived by solving a constrained quadratic programming (QP) problem. The CLF and CBF respectively characterize the stability objective and the safety objective for the nonlinear control systems. These objectives imply important properties including controllability, convergence, and robustness of control problems. Under this framework, optimal control corresponds to the minimal solution to a constrained QP problem. When uncertainties are explicitly considered, the setting of the CLF and CBF is proposed to study the input-to-state stability and input-to-state safety and to analyze the effect of disturbances. The recent theoretic progress and novel applications of CLF and CBF are systematically reviewed and discussed in this paper. Finally, we provide research directions that are significant for the advance of knowledge in this area.

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http://hdl.handle.net/10453/174650