This paper presents a novel approach for achieving safe stochastic optimal control in networked multi-agent systems (MASs). The proposed method incorporates barrier states (BaSs) into the system dynamics to embed safety constraints. To accomplish this, the networked MAS is factorized into multiple subsystems, and each one is augmented with BaSs for the central agent. The optimal control law is obtained by solving the joint Hamilton-Jacobi-Bellman (HJB) equation on the augmented subsystem, which guarantees safety via the boundedness of the BaSs. The BaS-based optimal control technique yields safe control actions while maintaining optimality. The safe optimal control solution is approximated using path integrals. To validate the effectiveness of the proposed approach, numerical simulations are conducted on a cooperative UAV team in two different scenarios.

翻译：本文提出了一种实现网络化多智能体系统（MASs）安全随机最优控制的新方法。所提方法将势垒状态（BaSs）引入系统动力学方程以嵌入安全约束。为此，将网络化MAS分解为多个子系统，并为每个子系统的中心智能体增广势垒状态。通过求解增广子系统上的联合哈密顿-雅可比-贝尔曼（HJB）方程获得最优控制律，该控制律通过势垒状态的有界性保证系统安全。基于势垒状态的最优控制技术能在保持最优性的同时产生安全控制动作。采用路径积分方法逼近安全最优控制解。为验证所提方法的有效性，在两种不同场景下对合作无人机编队进行了数值仿真。