A survey on iterative learning control with randomly varying trial lengths: Model, synthesis, and convergence analysis

D Shen, X Li - Annual Reviews in Control, 2019 - Elsevier
The nonuniform trial length problem, which causes information dropout in learning, is very
common in various control systems such as robotics and motion control systems. This paper …

Iterative learning control with incomplete information: A survey

D Shen - IEEE/CAA Journal of Automatica Sinica, 2018 - ieeexplore.ieee.org
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 …

A technical overview of recent progresses on stochastic iterative learning control

D Shen - Unmanned Systems, 2018 - World Scientific
This paper contributes to a technical overview of recent progresses on stochastic iterative
learning control (ILC), where stochastic ILC implies the learning control for systems with …

Iterative learning control for discrete nonlinear systems with randomly iteration varying lengths

D Shen, W Zhang, JX Xu - Systems & Control Letters, 2016 - Elsevier
This note proposes ILC for discrete-time affine nonlinear systems with randomly iteration
varying lengths. No prior information on the probability distribution of random iteration length …

A novel Markov chain based ILC analysis for linear stochastic systems under general data dropouts environments

D Shen, JX Xu - IEEE Transactions on Automatic Control, 2016 - ieeexplore.ieee.org
This technical note contributes to the convergence analysis for iterative learning control
(ILC) for linear stochastic systems under general data dropout environments, ie, data …

[HTML][HTML] Iterative learning control for intermittently sampled data: Monotonic convergence, design, and applications

N Strijbosch, T Oomen - Automatica, 2022 - Elsevier
The standard assumption that a measurement signal is available at each sample in iterative
learning control (ILC) is not always justified, eg, when exploiting time-stamped data from …

Two updating schemes of iterative learning control for networked control systems with random data dropouts

D Shen, C Zhang, Y Xu - Information Sciences, 2017 - Elsevier
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 …

Data-driven learning control for stochastic nonlinear systems: Multiple communication constraints and limited storage

D Shen - IEEE Transactions on Neural Networks and Learning …, 2017 - ieeexplore.ieee.org
This paper proposes a data-driven learning control method for stochastic nonlinear systems
under random communication conditions, including data dropouts, communication delays …

Iterative learning tracking for multisensor systems: A weighted optimization approach

D Shen, C Liu, L Wang, X Yu - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Multisensor systems are widely applied to realize the comprehensive monitoring and control
as they feature multiple individual sensors/outputs. In such systems, different sensors can …

Optimal input filtering for networked iterative learning control systems with packet dropouts and channel noises in both sides

L Huang, L Sun, T Wang, Q Zhang, J Li… - … Journal of Robust …, 2022 - Wiley Online Library
This article is concerned with the convergence performance of wireless networked iterative
learning control (ILC) systems with data dropouts and channel noises in both sensor‐to …