Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 171 tok/s
Gemini 2.5 Pro 47 tok/s Pro
GPT-5 Medium 32 tok/s Pro
GPT-5 High 36 tok/s Pro
GPT-4o 60 tok/s Pro
Kimi K2 188 tok/s Pro
GPT OSS 120B 437 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Control Barrier Functions for Linear Continuous-Time Input-Delay Systems with Limited-Horizon Previewable Disturbances (2403.04243v1)

Published 7 Mar 2024 in eess.SY and cs.SY

Abstract: Cyber-physical and autonomous systems are often equipped with mechanisms that provide predictions/projections of future disturbances, e.g., road curvatures, commonly referred to as preview or lookahead, but this preview information is typically not leveraged in the context of deriving control barrier functions (CBFs) for safety. This paper proposes a novel limited preview control barrier function (LPrev-CBF) that avoids both ends of the spectrum, where on one end, the standard CBF approach treats the (previewable) disturbances simply as worst-case adversarial signals and on the other end, a recent Prev-CBF approach assumes that the disturbances are previewable and known for the entire future. Moreover, our approach applies to input-delay systems and has recursive feasibility guarantees since we explicitly take input constraints/bounds into consideration. Thus, our approach provides strong safety guarantees in a less conservative manner than standard CBF approaches while considering a more realistic setting with limited preview and input delays.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (15)
  1. M. Rungger and P. Tabuada, “Computing robust controlled invariant sets of linear systems,” IEEE Transactions on Automatic Control, vol. 62, no. 7, pp. 3665–3670, 2017.
  2. A. D. Ames, X. Xu, J. W. Grizzle, and P. Tabuada, “Control barrier function based quadratic programs for safety critical systems,” IEEE Trans. on Automatic Control, vol. 62, no. 8, pp. 3861–3876, 2016.
  3. A. D. Ames, S. Coogan, M. Egerstedt, G. Notomista, K. Sreenath, and P. Tabuada, “Control barrier functions: Theory and applications,” in European Control Conference (ECC).   IEEE, 2019, pp. 3420–3431.
  4. T. Pati and S. Z. Yong, “Robust control barrier functions for control affine systems with time-varying parametric uncertainties,” IFAC-PapersOnLine, pp. 11 356–11 362, 2023.
  5. M. Tomizuka and D. E. Whitney, “Optimal discrete finite preview problems (Why and how is future information important?),” Journal of Dynamic Systems, Measurement, and Control, vol. 97, no. 4, pp. 319–325, 12 1975.
  6. C. E. Garcia, D. M. Prett, and M. Morari, “Model predictive control: Theory and practice–A survey,” Automatica, vol. 25, no. 3, pp. 335–348, 1989.
  7. Z. Liu and N. Ozay, “On the value of preview information for safety control,” in American Control Conference (ACC).   IEEE, 2021, pp. 2348–2354.
  8. Z. Liu, L. Yang, and N. Ozay, “Scalable computation of controlled invariant sets for discrete-time linear systems with input delays,” in American Control Conference (ACC).   IEEE, 2020, pp. 4722–4728.
  9. J. Breeden and D. Panagou, “Predictive control barrier functions for online safety critical control,” in IEEE Conference on Decision and Control (CDC).   IEEE, 2022, pp. 924–931.
  10. T. Pati, S. Hwang, and S. Z. Yong, “Preview control barrier functions for linear continuous-time systems with previewable disturbances,” in 2023 European Control Conference (ECC).   IEEE, 2023, pp. 1–7.
  11. M. Jankovic, “Control barrier functions for constrained control of linear systems with input delay,” in American control conference (ACC).   IEEE, 2018, pp. 3316–3321.
  12. A. Singletary, Y. Chen, and A. D. Ames, “Control barrier functions for sampled-data systems with input delays,” in IEEE Conference on Decision and Control (CDC).   IEEE, 2020, pp. 804–809.
  13. C. Ott, R. Mukherjee, and Y. Nakamura, “Unified impedance and admittance control,” in IEEE International Conference on Robotics and Automation.   IEEE, 2010, pp. 554–561.
  14. T. T. Andersen, H. B. Amor, N. A. Andersen, and O. Ravn, “Measuring and modelling delays in robot manipulators for temporally precise control using machine learning,” in IEEE International Conference on Machine Learning and Applications.   IEEE, 2015, pp. 168–175.
  15. J. Hunt and H. Lee, “A new parallel actuated architecture for exoskeleton applications involving multiple degree-of-freedom biological joints,” Journal of Mechanisms and Robotics, vol. 10, no. 5, p. 051017, 2018.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.