High-speed rail (HSR) has brought a number of social and economic benefits, such as
shorter trip times for journeys of between one and five hours; safety, security, comfort and on …

Railway system performances depend on effective dynamic scheduling and train operation
control. The fast expansion and increasing complexity of high-speed railway (HSR) networks …

Automation is expected to effectively address the growing demand for passenger and freight
transportation, safety issues, human errors, and increasing congestion. The growth of …

For enhancing the operation efficiency of the fully automatic operation (FAO) system in the
urban rail transit (URT), this paper investigates the robust dynamic train regulation problem …

In this article, an echo state network (ESN)-based backstep** adaptive iterative learning
control scheme is proposed for nonlinear strict-feedback systems performing the same …

The energy-efficient train operation methodology is the focus of this paper, and a Q-Learning-
based eco-driving approach is proposed. Firstly, the core idea of energy-distribution-based …

In this brief, we develop a novel iterative learning control (ILC) algorithm to deal with
trajectory tracking problems for a class of unicycle-type mobile robots with two actuated …

This article investigates the problem of event-triggered model-free adaptive iterative learning
control (MFAILC) for a class of nonlinear systems over fading channels. The fading …

In this paper, a novel mixed iterative adaptive dynamic programming (ADP) algorithm is
developed to solve the optimal battery energy management and control problem in smart …

This paper presents a robust event-triggered model predictive control (MPC) strategy for
multiple high-speed trains (MHSTs) with random switching topologies. Due to the …