Event‐Triggered Iterative Learning Control for Multi‐Agent Systems With Dos Attacks Under a Two‐Dimensional Framework

ABSTRACT This article focuses on linear multi‐agent systems (MAS) subject to Denial‐of‐Service (DoS) attacks on the input/output (I/O) sides under a fading channel environment. An iterative learning control (ILC) algorithm with the event‐triggered scheme is developed. Firstly, the process of DoS attacks is formulated by mutually independent Bernoulli sequences with known mean and variance. Then the fading measurements in the I/O channels are characterized as independent Gaussian distributions with known mean and variance. For conserving network communication resources, an event triggering mechanism is employed to reduce the number of controller updates. Subsequently, the repeating system and the presented ILC algorithm involving both iteration axis and time axis are converted into a stochastic 2D Roesser model. Based on the 2D theory, the stability criteria of the system are further derived, the design scheme for controller gains is proposed, and the gains are solved by the LMI technique. To mitigate the adverse effects induced by stochastic fading, an ILC algorithm with a compensation mechanism is proposed, and rigorous theoretical analyses are conducted. Finally, numerical simulations are established to confirm that the presented control algorithm is effective.