In this paper, we study the resilient vector consensus problem in networks with adversarial agents and improve resilience guarantees of existing algorithms. A common approach to achieving resilient vector consensus is that every non-adversarial (or normal) agent in the network updates its state by moving towards a point in the convex hull of its normal neighbors’ states. Since an agent cannot distinguish between its normal and adversarial neighbors, computing such a point, often called safe point, is a challenging task.

Automatica

110046

https://www.sciencedirect.com/science/article/pii/S0005109821005744