Results 301 to 310 of about 816,103 (361)

Disturbance rejection based on iterative learning control with extended state observer for a four-degree-of-freedom hybrid magnetic bearing system

, 2021
Iterative learning control (ILC) is an iterative control strategy which calculates a new input according to the error in previous cycles. It is widely used in industries with repetitive operations.
Xiaodong Sun, Jin Zhijia, Long Chen, Zebin Yang   +3 more
semanticscholar   +1 more source

Iterative Learning Control for Video-Rate Atomic Force Microscopy

IEEE/ASME transactions on mechatronics, 2021
We present a control scheme for video-rate atomic force microscopy with rosette pattern. The controller structure involves a feedback internal-model-based controller and a feedforward iterative learning controller.
N. Nikooienejad, M. Maroufi, R. Moheimani   +2 more
semanticscholar   +1 more source

Safety-Critical Model-Free Adaptive Iterative Learning Control for Multi-Agent Consensus Using Control Barrier Functions

IEEE Transactions on Circuits and Systems - II - Express Briefs
Aiming at the problem of safety of unknown multi-agent systems in the process of executing repetitive tasks, an novel iterative learning control barrier functions is proposed in this brief.
Shuaiming Yan, Lei Shi, Hao Zhang, Shaojie Yao, Yi Zhou   +4 more
semanticscholar   +1 more source

Human-in-The-Loop Fuzzy Iterative Learning Control of Consensus for Unknown Mixed-Order Nonlinear Multi-Agent Systems

IEEE transactions on fuzzy systems
This article studies the human-in-the-loop fuzzy iterative learning control of leader-following consensus for unknown mixed-order nonlinear multi-agent systems.
Jiaxi Chen, J. Xie, Junmi Li, Weisheng Chen   +3 more
semanticscholar   +1 more source

Robust Adaptive Iterative Learning Control for a Generic Class of Uncertain Non-Square MIMO Systems

IEEE Transactions on Automatic Control
In this work, the adaptive iterative learning control (AILC) for a generic class of nonsquare nonlinear systems is investigated in presence of unknown control gain matrices and nonparametric iteration-varying uncertainties.
Xuefang Li, Zhongsheng Hou
semanticscholar   +1 more source

RBFNN-Based Data-Driven Predictive Iterative Learning Control for Nonaffine Nonlinear Systems

IEEE Transactions on Neural Networks and Learning Systems, 2020
In this paper, a novel data-driven predictive iterative learning control (DDPILC) scheme based on a radial basis function neural network (RBFNN) is proposed for a class of repeatable nonaffine nonlinear discrete-time systems subjected to nonrepetitive ...
Qiongxia Yu, Z. Hou, Xuhui Bu, Qiongfang Yu   +3 more
semanticscholar   +1 more source

Iterative Learning Control of Constrained Systems With Varying Trial Lengths Under Alignment Condition

IEEE Transactions on Neural Networks and Learning Systems, 2021
This brief is concerned with iterative learning control (ILC) of constrained multi-input multi-output (MIMO) nonlinear systems under the state alignment condition with varying trial lengths.
M. Shen, Xingzheng Wu, Ju H. Park, Yang Yi, Yonghui Sun   +4 more
semanticscholar   +1 more source

An iterative learning controller with initial state learning

IEEE Transactions on Automatic Control, 1999
In iterative learning control (ILC), a common assumption is that the initial states in each repetitive operation should be inside a given ball centred at the desired initial states which may be unknown. This assumption is critical to the stability analysis, and the size of the ball will directly affect the final output trajectory tracking errors.
YangQuan Chen, Changyun Wen, Zhiming Gong, Mingxuan Sun   +3 more
openaire   +1 more source

Iterative Learning Control for Output Tracking of Nonlinear Systems With Unavailable State Information

IEEE Transactions on Neural Networks and Learning Systems, 2021
This work presents a novel design framework of adaptive iterative learning control (ILC) approach for a class of uncertain nonlinear systems. By using the closed-loop reference model that can be viewed as an observer, the proposed adaptive ILC approach ...
Xuefang Li, D. Shen, Beichen Ding
semanticscholar   +1 more source

Adaptive iterative learning control for discrete‐time nonlinear systems with multiple iteration‐varying high‐order internal models

International Journal of Robust and Nonlinear Control, 2021
In this work, an adaptive iterative learning control (AILC) method is designed for a class of parametric discrete‐time nonlinear systems with random initial condition, unknown time‐varying input gain and multiple time‐iteration‐varying factors including ...
Miao Yu, Sheng Chai
semanticscholar   +1 more source