Finite-Time Resilient Formation Control with Bounded Inputs
It addresses the problem of safe multi-agent formation control in adversarial environments, but the results are incremental as they extend existing resilient control methods to include input bounds and finite-time convergence.
This paper introduces a novel continuous-time resilient controller for multi-agent formation control that guarantees finite-time convergence under bounded inputs and adversarial agents, using a norm-based filtering mechanism and a graph structure called Resilient Directed Acyclic Graph (RDAG).
In this paper we consider the problem of a multi-agent system achieving a formation in the presence of misbehaving or adversarial agents. We introduce a novel continuous time resilient controller to guarantee that normally behaving agents can converge to a formation with respect to a set of leaders. The controller employs a norm-based filtering mechanism, and unlike most prior algorithms, also incorporates input bounds. In addition, the controller is shown to guarantee convergence in finite time. A sufficient condition for the controller to guarantee convergence is shown to be a graph theoretical structure which we denote as Resilient Directed Acyclic Graph (RDAG). Further, we employ our filtering mechanism on a discrete time system which is shown to have exponential convergence. Our results are demonstrated through simulations.