Artificial neural networks (ANN) provide a range of powerful new techniques for solving
problems in sensor data analysis, fault detection, process identification, and control and …

Polymerization process can be classified as a nonlinear type process since it exhibits a
dynamic behaviour throughout the process. Therefore, it is highly complicated to obtain an …

Controlling batch polymerization reactors imposes great operational difficulties due to the
complex reaction kinetics, inherent process nonlinearities and the continuous demand for …

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

Based on a two-dimensional (2D) system description of a batch process in industry, a robust
closed-loop iterative learning control (ILC) scheme is proposed for batch processes with …

Abstract Run-to-run (R2R) control is widely used in semiconductor manufacturing systems to
minimize the process drift, shift and variability. The R2R controller adjusts control actions or …

Nowadays existing technological process management systems increasingly require the
development of criteria related to ensuring the quantity, quality and technological safety …

Integrated operational decision-making in chemical plants is important for improving
profitability. Integrated scheduling and control frameworks have been developed to enhance …

For industrial nonlinear batch processes that can be practically divided into a series of
piecewise affine operating regions, a two-dimensional (2D) closed-loop iterative learning …

This paper proposes the design of the integrated output feedback and iterative learning
control (ILC) for batch processes with uncertain perturbations and interval time-varying …