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Enhancing Robustness of Control Barrier Function: A Reciprocal Resistance-based Approach

  • Xinming Wang
  • , Zongyi Guo
  • , Jianguo Guo
  • , Jun Yang
  • , Yunda Yan
  • Cardiff University
  • Northwestern Polytechnical University Xian
  • The Hong Kong University of Science and Technology (Guangzhou)
  • University College London

科研成果: 期刊稿件文章同行评审

摘要

In this note, a new reciprocal resistance-based control barrier function (RRCBF) is developed to enhance the robustness of control barrier functions for disturbed affine nonlinear systems, without requiring explicit knowledge of disturbance bounds. By integrating a reciprocal resistance-like term into the conventional zeroing barrier function framework, we formally establish the concept of the reciprocal resistance-based barrier function (RRBF), rigorously proving the forward invariance of its associated safe set and its robustness against bounded disturbances. The RRBF inherently generates a buffer zone near the boundary of the safe set, effectively dominating the influence of uncertainties and external disturbances. This foundational concept is extended to formulate RRCBFs, including their high-order variants. To alleviate conservatism in the presence of complex, time-varying disturbances, we further introduce a disturbance observer-based RRCBF (DO-RRCBF), which exploits disturbance estimates to enhance safety guarantee and recover nominal control performance. The effectiveness of the proposed framework is validated through two simulation studies: a double-integrator linear system illustrating forward invariance in the phase plane, and an adaptive cruise control scenario demonstrating robustness in systems with high relative degree.

源语言英语
期刊IEEE Transactions on Automatic Control
DOI
出版状态已接受/待刊 - 2026

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