Objectives, challenges, and prospects of batch processes: Arising from injection molding applications

Y Zhou, Z Cao, J Lu, C Zhao, D Li, F Gao - Korean Journal of Chemical …, 2022 - Springer
Injection molding, a polymer processing technique that converts thermoplastics into a variety
of plastic products, is a complicated nonlinear dynamic process that interacts with a different …

High-order model-free adaptive iterative learning control of pneumatic artificial muscle with enhanced convergence

Q Ai, D Ke, J Zuo, W Meng, Q Liu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Pneumatic artificial muscles (PAMs) have been widely used in actuation of medical devices
due to their intrinsic compliance and high power-to-weight ratio features. However, the …

Resilient model-free adaptive iterative learning control for nonlinear systems under periodic DoS attacks via a fading channel

W Yu, R Wang, X Bu, Z Hou… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This article studies the resilient control problem for a class of unknown nonlinear systems
with fading measurements under malicious denial-of-service (DoS) attacks. The system …

Discrete-time extended state observer-based model-free adaptive control via local dynamic linearization

R Chi, Y Hui, S Zhang, B Huang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Linearization is often used for control design of nonlinear systems but what degree of a
linearization is sufficient for the controller design is always a question. Furthermore, most of …

Extended state observer-based data-driven iterative learning control for permanent magnet linear motor with initial shifts and disturbances

Y Hui, R Chi, B Huang, Z Hou - IEEE Transactions on Systems …, 2019 - ieeexplore.ieee.org
In this paper, an extended state observer-based data-driven iterative learning control
[extended state observer (ESO)-based DDILC] is developed for a permanent magnet linear …

Data-driven iterative learning control for nonlinear discrete-time MIMO systems

X Yu, Z Hou, MM Polycarpou… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article considers the tracking control of unknown nonlinear nonaffine repetitive discrete-
time multi-input multi-output systems. Two data-driven iterative learning control (ILC) …

Robust optimization-based iterative learning control for nonlinear systems with nonrepetitive uncertainties

D Meng, J Zhang - IEEE/CAA Journal of Automatica Sinica, 2021 - ieeexplore.ieee.org
This paper aims to solve the robust iterative learning control (ILC) problems for nonlinear
time-varying systems in the presence of nonrepetitive uncertainties. A new optimization …

Iterative-learning error compensation for autonomous parking of mobile manipulator in harsh industrial environment

J Meng, S Wang, G Li, L Jiang, X Zhang, C Liu… - Robotics and Computer …, 2021 - Elsevier
In wide-area and multi-sites manufacturing scenarios, the mobile manipulator suffers from
inadequate autonomous parking performance due to the harsh industrial environment …

Data-driven feedforward learning with force ripple compensation for wafer stages: A variable-gain robust approach

F Song, Y Liu, W Jin, J Tan, W He - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
To meet the increasing demand for denser integrated circuits, feedforward control plays an
important role in the achievement of high servo performance of wafer stages. The …

A probabilistically quantized learning control framework for networked linear systems

D Shen, N Huo, SS Saab - IEEE transactions on neural …, 2021 - ieeexplore.ieee.org
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 …