Faded Communication-Based Coordinated Model-Free Adaptive Iterative Learning Control of Multiple HSTs Against Denial-of-Service Attacks

The paper studies the faded communication-based coordinated model-free adaptive iterative learning control (MFAILC) of multiple high-speed trains (MHSTs) against periodic denial-of-service (PDoS) attacks. First, considering the nonlinearity and uncertainty of the train operation, the dynamic model of MHSTs is constructed, and then followed by the newly established linear data-relationship model. Next, the random faded channel is expressed by Rice fading model, and the PDoS attacks are introduced with the help of the random coefficients. After giving the theoretical analysis, the compensation scheme is conducted, and the research is further extended to the switching topologies. Finally, a set of numerical tests is conducted to confirm the practicability of the MFAILC approaches. Note to Practitioners—HSTs have the characteristics of high speed, high safety, etc. The practical problems that motivate this work are the complexity of train model, the instability of the networks and the urgent requirement to further improve the operation efficiency. Meanwhile, the possible application areas include the automatic operation of HSTs and the cooperative operation of train groups. Specifically, the potential of this work includes: 1) eliminating the requirement of detailed modeling of train dynamics; 2) providing a theoretical basis for reliable train operation in an unstable network environment, and 3) improving the efficiency of train group operation through cooperation. Nevertheless, the limitation of this paper is that the results have not been verified on the actual trains and railways. To extend it to be more practical, we will further investigate more practical constraints in the train operation environment, such as the constraints of the traction network, the constraints of the track adhesion condition, and also continue to optimize the controller parameters iteratively.