Permanent magnet synchronous motors (PMSMs) are commonly used in the automation
industry. With the speedy development of digital system processors, predictive control as a …

This paper addresses control performance monitoring (CPM) and degradation recovering in
automatic control systems. It begins with a re-visit of CPM techniques and a summary of the …

This work considers a seeded fesoterodine fumarate (FF) cooling crystallization and
presents the methodology and implementation of a real‐time machine learning modeling …

The performance of a standard model predictive controller (MPC) is directly related to its
predictive model. If there are unmodeled periodic disturbances in the actual system, MPC …

Iterative learning model predictive control (ILMPC), endowed with the merits of iterative
learning control and model predictive control, has excellent abilities of disturbance rejection …

Iterative learning model predictive control (ILMPC) has been recognized as an effective
approach to realize high-precision tracking for batch processes with repetitive nature …

We propose a generic nonlinear reduced-order tracking control method for elastic soft
robots. To this end, a new linear parameter varying (LPV) control framework is developed …

For nonlinear batch processes with uncertainties, disturbances and partial actuator faults, an
iterative learning robust predictive fault-tolerant control approach is developed. Based on …

The work deals with composite iterative learning model predictive control (CILMPC) for
uncertain batch processes via a two dimensional Fornasini–Marchesini (2D-FM) model. A …

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 …