The article discusses the use of Gaussian processes to address model uncertainty in high-order control barrier functions (HOCBFs). It highlights the challenges posed by model uncertainty in ensuring system safety and introduces a data-driven approach to handle these uncertainties. The paper presents a method to convert chance constraints of HOCBFs into second-order cone constraints, enabling convex constrained optimization for safety filtering. The effectiveness of the proposed strategy is validated through numerical results. The study focuses on two main applications: adaptive cruise control with collision avoidance and an active suspension system. Simulation results demonstrate the superiority of the GP-based SOCP-HOCBF design over nominal QP-HOCBF controllers in maintaining system safety and performance.
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by Mohammad Aal... at arxiv.org 03-15-2024
https://arxiv.org/pdf/2403.09573.pdfDeeper Inquiries