In this paper, we present two iterative learning control (ILC) frameworks for tracking
problems with specified data points that are desired points at certain time instants. To design …

The paper describes a substantial extension of norm optimal iterative learning control
(NOILC) that permits tracking of a class of finite dimensional reference signals whilst …

A new improved data-driven optimal TILC (DDOTILC) is proposed for a class of nonlinear
discrete-time systems by using time-varying control input signals to enhance control …

In this paper, a novel neural network based terminal iterative learning control method is
proposed for a class of uncertain nonlinear non‐affine systems to track run‐varying …

This paper presents a new optimization-based iterative learning control (ILC) framework for
multiple-point tracking control. Conventionally, one demand prior to designing ILC …

This paper presents a new data-driven optimal design framework of point-to-point iterative
learning control (PTP-ILC), where the control signal is directly updated from the errors of …

In this paper, we present two iterative learning control (ILC) frameworks for multiple points
tracking problems. First, we present an ILC scheme to produce output curves that pass close …

В работе показано, что сегодня происходит существенное снижение эффективности
использования системы планово-предупредительного ремонта электрооборудования …

In many industries there are technological processes that are cyclical in nature. In the control
of such processes, the high-efficiency method has been demonstrated by the method of …

Repetitive control and iterative learning control are both learning control schemes which
update and refine control sequence using tracking errors in past trials. With the superior …