The cement kiln is one of the major energy-intense processes that need efficient controllers
to minimise fuel consumption, enhance clinker production, and improve cement quality. A …

This paper presents a framework to refine identified artificial neural networks (ANN) based
state-space linear parameter-varying (LPV-SS) models with closed-loop data using online …

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

This paper investigates a novel offset-free control scheme based on a multiple model
predictive controller (MMPC) and an adaptive integral action controller for nonlinear …

An adaptive steady state constrained autoregressive with extra input (SSARX) model is
developed and embedded into a model predictive control (MPC) framework to regulate a …

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) …

Optimal control of cement kiln is demanding to ensure cement quality and minimal energy
usage in cement industries. Plant-model mismatch (PMM) in the prediction model …

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 …

The assessment and diagnosis of controller performance for model‐based closed‐loop
control systems has received considerable attention in recent years. A recognized factor …