Obstacle Avoidance and Safe Coverage of Moving Domains for Multiagent Systems via Adaptive Control Barrier Function

This article investigates the problem of safe coverage for multiagent systems with parameter uncertainties. A novel distributed control strategy is proposed to simultaneously guarantee safety and coverage for multiagent systems based on adaptive artificial potential function (AAPF) and adaptive control barrier function (ACBF). In particular, a logic switching mechanism based on multiple identification models is integrated into a coverage controller while the transient performance of multiagent systems is effectively improved. Also, a framework for safe coverage in multiagent systems is presented in the context of parametric uncertainties. In this framework, a nominal controller is obtained by using the AAPF method. Furthermore, the nominal controller undergoes modification through the application of ACBF based on quadratic programs to achieve safe coverage. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control strategy.

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Institutions

Publication Details

Journal
IEEE Transactions on Systems Man and Cybernetics Systems
Published
2025-04-25
DOI
https://doi.org/10.1109/tsmc.2025.3561205
Citations
1
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
1.49

Funders

Controls
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article

Obstacle Avoidance and Safe Coverage of Moving Domains for Multiagent Systems via Adaptive Control Barrier Function

Lijun Long, S. Wu
1 citations
IEEE Transactions on Systems Man and Cybernetics Systems
Distributed Control Multi-Agent Systems
1.49
article

Obstacle Avoidance and Safe Coverage of Moving Domains for Multiagent Systems via Adaptive Control Barrier Function

Lijun Long, S. Wu
article en
1 citations

Abstract

This article investigates the problem of safe coverage for multiagent systems with parameter uncertainties. A novel distributed control strategy is proposed to simultaneously guarantee safety and coverage for multiagent systems based on adaptive artificial potential function (AAPF) and adaptive control barrier function (ACBF). In particular, a logic switching mechanism based on multiple identification models is integrated into a coverage controller while the transient performance of multiagent systems is effectively improved. Also, a framework for safe coverage in multiagent systems is presented in the context of parametric uncertainties. In this framework, a nominal controller is obtained by using the AAPF method. Furthermore, the nominal controller undergoes modification through the application of ACBF based on quadratic programs to achieve safe coverage. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control strategy.

IEEE Transactions on Systems Man and Cybernetics SystemsVol. 55(7)
State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University (CN)
National Natural Science Foundation of China, Higher Education Discipline Innovation Project, Liaoning Revitalization Talents Program, Fundamental Research Funds for the Central Universities
Climate action
Openalex Percentile: Top 18%
Distributed Control Multi-Agent Systems
1.49
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