A PD-type state-dependent Riccati equation with iterative learning augmentation for mechanical systems
This work proposes a novel proportional-derivative (PD)-type state-dependent Riccati
equation (SDRE) approach with iterative learning control (ILC) augmentation. On the one …
equation (SDRE) approach with iterative learning control (ILC) augmentation. On the one …
Iterative learning control of constrained systems with varying trial lengths under alignment condition
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 …
output (MIMO) nonlinear systems under the state alignment condition with varying trial …
Data-based security fault tolerant iterative learning control under denial-of-service attacks
Z Li, C Zhou, W Che, C Deng, X Jin - Actuators, 2022 - mdpi.com
This paper mainly studies the data-based security fault tolerant iterative learning control
(SFTILC) problem of nonlinear networked control systems (NCSs) under sensor failures and …
(SFTILC) problem of nonlinear networked control systems (NCSs) under sensor failures and …
Performance improvement of low-cost iterative learning-based fuzzy control systems for tower crane systems
This paper is dedicated to the memory of Prof. Ioan Dzitac, one of the fathers of this journal
and its founding Editor-in-Chief till 2021. The paper addresses the performance …
and its founding Editor-in-Chief till 2021. The paper addresses the performance …
A Hierarchical Distributed Data-Driven Adaptive Learning Control for Nonaffine Nonlinear MASs
YS Ma, WW Che - IEEE Transactions on Neural Networks and …, 2024 - ieeexplore.ieee.org
This article designs a new hierarchical distributed data-driven adaptive learning control
algorithm to accomplish the leader-following tracking control objective for nonaffine …
algorithm to accomplish the leader-following tracking control objective for nonaffine …
An indirect iterative learning controller for nonlinear systems with mismatched uncertainties and matched disturbances
T Thanh Cao, P Doan Nguyen… - … Journal of Systems …, 2022 - Taylor & Francis
The article proposes an intelligent controller for output regulation of nonlinear non-
autonomous continuous-time systems with mismatched uncertainties and matched …
autonomous continuous-time systems with mismatched uncertainties and matched …
Sampled-Data Adaptive Iterative Learning Control for Uncertain Nonlinear Systems
Y Hui, D Meng, R Chi, K Cai - IEEE Transactions on Systems …, 2024 - ieeexplore.ieee.org
In the realm of data-driven adaptive iterative learning control (AILC), the emphasis in
designing and analyzing control schemes mainly concentrates on discrete-time systems …
designing and analyzing control schemes mainly concentrates on discrete-time systems …
Quantized data‐based iterative learning control under denial‐of‐service attacks
CR Zhou, WW Che - Optimal Control Applications and Methods, 2023 - Wiley Online Library
This article mainly studies the quantized data‐based iterative learning tracking control
(QDBILTC) problem of nonlinear networked control systems in the presence of signals …
(QDBILTC) problem of nonlinear networked control systems in the presence of signals …
Data-driven iterative learning control of nonlinear systems by adaptive model matching
Iterative learning control (ILC) has proven successful in the industry for enhancing tracking
performance of repetitive tasks. The high accuracy and fast convergence of ILC algorithms …
performance of repetitive tasks. The high accuracy and fast convergence of ILC algorithms …
Data-Driven Internal Model Learning Control for Nonlinear Systems
H Zhang, R Chi, B Huang - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
A novel data-driven internal model learning control (DIMLC) strategy is developed for a
nonlinear nonaffine system subject to unknown nonrepetitive uncertainties. At first, an …
nonlinear nonaffine system subject to unknown nonrepetitive uncertainties. At first, an …