Because of the increasing complexity and nonlinearity of industrial processes, nonlinear
model predictive control (NMPC) has been rapidly developed owing to its fast response and …

The transition from batch to continuous processes in the pharmaceutical industry has been
driven by the potential improvement in process controllability, product quality homogeneity …

This article addresses the plant-model mismatch detection problem for linear multiple-input
and multiple-output systems operating under the constrained dynamic matrix control (DMC) …

This article addresses the plant‐model mismatch estimation problem for linear multiple‐
input and multiple‐output systems operating under the dynamic matrix control (DMC) …

The area of controller performance monitoring, assessment, and diagnosis for model
predictive control (MPC) has seen an increase in interest in recent years. A frequently …

For the model plant mismatch (MPM) assessment of MPC systems, a correlation analysis
method between the input and the disturbance (CAID) is proposed and is combined with …

Updating the process model remains an important concern in practical implementations of
Model Predictive Control (MPC). This work introduces a novel stochastic model predictive …

A new event-triggered model predictive control (MPC) method is proposed for PWA systems
with model-plant mismatch, such that, for a given asymptotically constant reference signal …

This paper investigates the distributed model predictive control (DMPC) for positive systems
with interval and polytopic uncertainties, respectively. Different from the traditional quadratic …

In this article, a novel approach is proposed for integrating a Biologically-Inspired Optimal
Control Strategy (BIOsingle bondCS) with an Artificial Neural Network (ANN)-based …