Distributed Model Free Adaptive Iterative Learning Control of Multiple HSTs Under DoS Attacks

This paper studies the distributed model free adaptive iterative learning control (MFAILC) of multiple high-speed trains (MHSTs) under malicious denial-of-service (DoS) attacks. By using the equivalent linearization technique, the discrete-time dynamic model of MHSTs is firstly converted into a linear data-based one. Then, the strategy of DoS attacker is introduced, which is represented by a Bernoulli variable with unknown mathematical expectation. Next, the distributed MFAILC scheme is conducted, which belongs to the scope of data-driven approach. Finally, the stability of MHSTs is studied and the validity of the MFAILC is confirmed by a numerical test.