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Control Barrier Functions for Sampled-Data Systems with Input Delays

Singletary, Andrew and Chen, Yuxiao and Ames, Aaron D. (2020) Control Barrier Functions for Sampled-Data Systems with Input Delays. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20200707-105249603

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Abstract

This paper considers the general problem of transitioning theoretically safe controllers to hardware. Concretely, we explore the application of control barrier functions (CBFs) to sampled-data systems: systems that evolve continuously but whose control actions are computed in discrete time-steps. While this model formulation is less commonly used than its continuous counterpart, it more accurately models the reality of most control systems in practice, making the safety guarantees more impactful. In this context, we prove robust set invariance with respect to zero-order hold controllers as well as state uncertainty, without the need to explicitly compute any control invariant sets. It is then shown that this formulation can be exploited to address input delays in this system, with the result being CBF constraints that are affine in the input. The results are demonstrated in a high-fidelity simulation of an unstable Segway robotic system in real-time.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/2005.06418arXivDiscussion Paper
ORCID:
AuthorORCID
Singletary, Andrew0000-0001-6635-4256
Chen, Yuxiao0000-0001-5276-7156
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20200707-105249603
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200707-105249603
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104246
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:07 Jul 2020 17:59
Last Modified:03 Aug 2020 21:17

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