Composite Learning Adaptive Safety Critical Control With Application to Adaptive Cruise of Intelligent Vehicles

This article presents an adaptive safety critical control scheme for uncertain systems with potentially conflicting control objective and safety constraint. The modified control barrier function (MCBF) is presented to rigorously guarantee the safety constraint subject to the unavoidable parameter es...

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Bibliographic Details
Published inIEEE transactions on industrial electronics (1982) pp. 1 - 11
Main Authors Shen, Jiajun, Liu, Yehui, Wang, Wei, Wang, Zhenqian
Format Journal Article
LanguageEnglish
Published IEEE 2025
Subjects
Adaptive control
adaptive cruise control
data-driven control
Electrical engineering
Electronic mail
Intelligent vehicles
Lyapunov methods
Parameter estimation
Safety
safety critical control
Uncertainty
Vectors
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ISSN0278-0046
1557-9948
DOI10.1109/TIE.2025.3555010

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Summary:This article presents an adaptive safety critical control scheme for uncertain systems with potentially conflicting control objective and safety constraint. The modified control barrier function (MCBF) is presented to rigorously guarantee the safety constraint subject to the unavoidable parameter estimation errors, then quadratic program (QP) is employed to synthesize the control Lyapunov function (CLF) and MCBF to form the certainty equivalence controller. Since the priority of CLF is regraded and the MCBF is designed to be nonpositive definite, we employ a separate parameter update module rather than the Lyapunov-based adaptive control approaches. The composite learning method is presented to eliminate the effects of parametric uncertainties without imposing the restrictive excitation conditions, further to avoid the conservative control performance. The experimental results of adaptive cruise for intelligent vehicles are provided to verify the theoretical findings.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2025.3555010