Objectives, challenges, and prospects of batch processes: Arising from injection molding applications
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 …
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
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 …
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
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 …
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 …
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
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 …
[extended state observer (ESO)-based DDILC] is developed for a permanent magnet linear …
Data-driven iterative learning control for nonlinear discrete-time MIMO systems
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) …
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 …
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
In wide-area and multi-sites manufacturing scenarios, the mobile manipulator suffers from
inadequate autonomous parking performance due to the harsh industrial environment …
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 …
important role in the achievement of high servo performance of wafer stages. The …
A probabilistically quantized learning control framework for networked linear systems
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 …
additive channel noise. Our objective is to achieve high tracking performance while reducing …