Safe Formation Control of Uncertain Multiagent Systems From a Bayesian Perspective

• 成果类型: Article
• 署名作者: Li, Boqian; Guo, Zhenyuan; Hu, Cheng; Zhu, Song; Wen, Shiping
• 署名单位: University of Technology Sydney; Hunan University; Xinjiang University; China University of Mining & Technology
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2024.3470928
• 发表日期: 2025
• 页码: 1929-1934
• 关键词: safety; Formation control; vectors; Bayes methods; uncertainty; optimization; Multi-agent systems; Gaussian Processes; Collision avoidance; Aerospace electronics; Bayesian optimization (BO); control barrier function; control Lyapunov function (CLF); Gaussian process (GP)

摘要

In this study, we address the formation control of uncertain multiagent systems with a safety requirement of collision avoidance. The control inputs are determined through quadratic programming (QP) solvers, where both the control Lyapunov function condition and control barrier function condition serve as constraints in the QP problem to achieve the control and safety objectives, respectively. In this work, the Bayesian theorem plays a crucial role in two key aspects. First, the unknown uncertainties are estimated using Gaussian process models, which provide mean and variance information incorporated into the QP framework to determine the control inputs. The integration ensures the attainment of desired objectives with high probability. Second, the Bayesian optimization algorithm is employed to optimize some hyperparameters. These selected hyperparameters enhance the solvability of the QP problem and simultaneously improve the control performance of multiagent systems.