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.
Authors
- Lijun Long (ORCID: https://orcid.org/0000-0003-2950-2410)
- S. Wu
Institutions
- State Key Laboratory of Synthetical Automation for Process Industries
- Northeastern University (CN)
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
- National Natural Science Foundation of China
- Higher Education Discipline Innovation Project
- Liaoning Revitalization Talents Program
- Fundamental Research Funds for the Central Universities