  This paper proposes a distributed cyber-attack detection method in
communication channels for a class of discrete, nonlinear, heterogeneous,
multi-agent systems that are controlled by our proposed formation-based
controller. A residual-based detection system, exploiting a neural network
(NN)-based observer, is developed to detect false data injection attacks on
agents communication channels. A Lyapunov function is used to derive the NN
weights tuning law and the attack detectability threshold. The uniform ultimate
boundedness (UUB) of the detector residual and formation error is proven based
on the Lyapunov stability theory. The proposed methods attack detectability
properties are analyzed, and simulation results demonstrate the proposed
detection methodologys performance.
