With the rapid development of communication, control and computer technologies in the last
several decades, automatic train operation (ATO), for which the driver no longer has to …

Iterative learning control (ILC) is suitable for systems that are able to repeatedly complete
several tasks over a fixed time interval. Since it was first proposed, ILC has been further …

Big data is becoming a research focus in intelligent transportation systems (ITS), which can
be seen in many projects around the world. Intelligent transportation systems will produce a …

During the past half century, modern control theory has developed greatly and many
branches and subfields have emerged, for example, linear system theory, optimal control …

In this paper, an adaptive iterative learning control (AILC) strategy for high-speed trains with
unknown speed delays and control input saturations is designed to address speed trajectory …

A model free adaptive iterative learning control based fault-tolerant control (MFAILC-FTC)
scheme for subway train speed tracking with speed sensor fault and over-speed protection …

Major difficulties and challenges of modern robotics systems focus on how to give robots self-
learning and self-decision-making ability. Visual servoing control strategy is an important …

Iterative learning control (ILC) is concerned with tracking a reference trajectory defined over
a finite time duration, and is applied to systems which perform this action repeatedly …

This article proposes a new spatial iterative learning control (ILC) algorithm that can track
the desired trajectory for operation control of high-speed train (HST) in the presence of time …

The precise tracking control of high-speed train is an essential prerequisite to ensure the
safety and comfort of the train. In this paper, an adaptive iterative learning control (ILC) …