Consensus conditions of continuous-time multi-agent systems under the $G$-expectation frame

Li Zhang, Shuai Liu, Xin Tai
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Abstract

In this paper, we consider the control problem of multi-agent systems with additive noises in the uncertain situation, (which means we are not sure about a particular probability space.) With mild condition, both $G$-mean square convergence and $G$-mean square steady-state error are analyzed by graph theory and $G$-martingale convergence. Different from classical probability, weak convergence in capacity and weak convergence in capacity 1 are considered.
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连续时间多智能体系统在$G$期望框架下的一致性条件
在本文中,我们考虑了不确定情况下(即我们不确定某个特定的概率空间)具有加性噪声的多智能体系统的控制问题。在温和条件下,利用图论和鞅收敛性分析了$G$-均方收敛性和$G$-均方稳态误差。与经典概率不同的是,它考虑了容量的弱收敛性和容量1的弱收敛性。
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