文献类型：期刊文献

英文题名：MPC-CBF Strategy for Multi-Agent System Obstacle Avoidance Path-Following

作者：Jia, Tinghan[1]; Yan, Huaicheng[1]; Shi, Yifan[1]; Wang, Li[1]; Wu, Yuyan[1]

机构：[1] Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China

年份：2025

起止页码：6088

外文期刊名：Chinese Control Conference, CCC

收录：EI(收录号：20254419432789)

语种：英文

外文关键词：Control theory - Intelligent agents - Model predictive control - Predictive control systems - Safety engineering - System stability

摘要：This paper presents a novel safety-critical distributed model predictive control method for multi-agent systems based on Control Barrier Functions (CBFs). Unlike traditional MPC approaches that rely on terminal constraints, a distributed Lyapunov-based model predictive control (DMPC) framework is proposed, which effectively decouples the optimization of system stability and performance. Within the DMPC framework, safety is guaranteed through the use of Control Barrier Function (CBF) constraints, leveraging the rolling horizon optimization of MPC to proactively avoid collisions. To reconcile the potential conflict between the stability and safety objectives of the MPC algorithm, slack variables are introduced into the CBF constraints. Finally, simulation studies on path following are conducted to validate the effectiveness of the proposed safety-critical robust control scheme. ? 2025 Technical Committee on Control Theory, Chinese Association of Automation.