Using Control Barrier Function in Distributed Explicit Reference Governor

This paper presents an explicit reference governor (ERG) design method, which incorporates control barrier function (CBF) and considers both non-convex and convex constraints in different parts of the system. Specifically, in the dynamic safety margin (DSM) of ERG, non-convex constraints are addressed, while in the navigation field (NF), convex constraints are handled with the assistance of CBF. Furthermore, this paper analyzes attitude tracking errors and constructs a robustness Lyapunov lower bound (RLLB) in the DSM, ensuring that safety constraints are satisfied even in the presence of attitude errors. Through this design, this paper offers a robust and safe reference control framework that effectively addresses flight control problems for UAVs in complex environments. Numerical simulations are provided to validate the efficacy of our proposed methodology.

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Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2025-06-19
DOI
https://doi.org/10.1109/taes.2025.3581182
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
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article

Using Control Barrier Function in Distributed Explicit Reference Governor

Weibin Cheng, Peng Wang
IEEE Transactions on Aerospace and Electronic Systems
Advanced Control Systems Optimization
article

Using Control Barrier Function in Distributed Explicit Reference Governor

Weibin Cheng, Peng Wang
article en

Abstract

This paper presents an explicit reference governor (ERG) design method, which incorporates control barrier function (CBF) and considers both non-convex and convex constraints in different parts of the system. Specifically, in the dynamic safety margin (DSM) of ERG, non-convex constraints are addressed, while in the navigation field (NF), convex constraints are handled with the assistance of CBF. Furthermore, this paper analyzes attitude tracking errors and constructs a robustness Lyapunov lower bound (RLLB) in the DSM, ensuring that safety constraints are satisfied even in the presence of attitude errors. Through this design, this paper offers a robust and safe reference control framework that effectively addresses flight control problems for UAVs in complex environments. Numerical simulations are provided to validate the efficacy of our proposed methodology.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(5)
Nanjing University of Aeronautics and Astronautics (CN)
Openalex Percentile: Top 84%
Advanced Control Systems Optimization
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