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Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models

Taylor, Andrew J. and Dorobantu, Victor D. and Cosner, Ryan K. and Yue, Yisong and Ames, Aaron D. (2022) Safety of Sampled-Data Systems with Control Barrier Functions via Approximate Discrete Time Models. . (Unpublished)

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Control Barrier Functions (CBFs) have been demonstrated to be a powerful tool for safety-critical controller design for nonlinear systems. Existing design paradigms do not address the gap between theory (controller design with continuous time models) and practice (the discrete time sampled implementation of the resulting controllers); this can lead to poor performance and violations of safety for hardware instantiations. We propose an approach to close this gap by synthesizing sampled-data counterparts to these CBF-based controllers using approximate discrete time models and Sampled-Data Control Barrier Functions (SD-CBFs). Using properties of a system's continuous time model, we establish a relationship between SD-CBFs and a notion of practical safety for sampled-data systems. Furthermore, we construct convex optimization-based controllers that formally endow nonlinear systems with safety guarantees in practice. We demonstrate the efficacy of these controllers in simulation.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Taylor, Andrew J.0000-0002-5990-590X
Dorobantu, Victor D.0000-0002-2797-7802
Cosner, Ryan K.0000-0002-4035-1425
Yue, Yisong0000-0001-9127-1989
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20220325-224027516
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114094
Deposited By: George Porter
Deposited On:28 Mar 2022 15:26
Last Modified:28 Mar 2022 15:26

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