This paper conducts a survey on iterative learning control (ILC) with incomplete information
and associated control system design, which is a frontier of the ILC field. The incomplete …

In this article, we consider quantized learning control for linear networked systems with
additive channel noise. Our objective is to achieve high tracking performance while reducing …

For unachievable tracking problems, where the system output cannot precisely track a given
reference, achieving the best possible approximation for the reference trajectory becomes …

This paper proposes two novel improved iterative learning control (ILC) schemes for
systems with randomly varying trial lengths. Different from the existing works on ILC with …

This article considers the zero-error tracking problem of quantized iterative learning control
for a general networked structure where the data are quantized and transmitted through …

A quantized iterative learning control (QILC) for continuous-time multi-agent systems with
finite-leveled sigma-delta (ΣA) quantization and random packet losses is first proposed in …

In this work, we propose a novel iterative learning control algorithm to deal with a class of
nonlinear systems with system output constraint requirements and quantization effects on …

The iterative learning control (ILC) problem is addressed in this paper for stochastic linear
systems with random data dropout modeled by a Bernoulli random variable. Both …

This article is concerned with the fixed time synchronization for a class of Quaternion valued
neural networks (QVNNs) with mixed time varying delays. Firstly, the QVNNs are separated …

This paper proposes a data-driven learning control method for stochastic nonlinear systems
under random communication conditions, including data dropouts, communication delays …