Control Barriers in Bayesian Learning of System Dynamics

This article focuses on learning a model of system dynamics online, while satisfying safety constraints. Our objective is to avoid offline system identification or hand-specified models and allow a system to safely and autonomously estimate and adapt its own model during operation. Given streaming o...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 68; H. 1; S. 214 - 229
Hauptverfasser:	Dhiman, Vikas, Khojasteh, Mohammad Javad, Franceschetti, Massimo, Atanasov, Nikolay
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Bayes methods Bayesian analysis Control barrier function (CBF) Control systems Gaussian process Gaussian processes high relative-degree system safety learning for dynamics and control Liapunov functions Machine learning Nonlinear control Nonlinear dynamical systems Probabilistic logic Safety self-triggered safe control Stability analysis Statistical analysis System dynamics System identification
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
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