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 …

For unachievable tracking problems, where the system output cannot precisely track a given
reference, achieving the best possible approximation for the reference trajectory becomes …

Iterative Learning Control (ILC) is known as a high-accuracy control strategy for repetitive
control missions of mechatronic systems. However, applying such learning controllers for …

The dielectric elastomer actuator (DEA) is an intelligent device with an actuation-sensing
integration capacity, which exhibits prospective applications in the field of soft robotics …

In batch processes, the ability to learn from previous process data results in high-value and
batch-improved products. For batch processes with constraints and state-dependent …

This paper proposes a latent variable nonlinear iterative learning model predictive control
method (LV-NILMPC) based on the dynamic fuzzy partial least squares (DFPLS) model to …

This article studies the conflicting goals of high-precision tracking and quick convergence
speed, which is a longstanding problem in the learning control of stochastic systems. In such …

In this article, we study the optimal iterative learning control (ILC) for constrained systems
with bounded uncertainties via a novel conic input mapping (CIM) design methodology. Due …

This article proposes a dynamic time warping (DTW)‐based iterative learning control (ILC)
scheme for discrete‐time nonlinear systems to tackle the path learning problem with varying …

In this study, we consider the learning-tracking problem for stochastic systems through
unreliable communication channels. The channels suffer from both multiplicative and …