The paper provides a review of the different approaches of Model Predictive Control (MPC)
to deal with the nonlinearities and transient behavior associated with pH and its control …

This article concerns a novel auxiliary-model-based expectation maximization (EM)
estimation method for Hammerstein systems with data loss by extending the EM method to …

This paper presents the development of data-driven hybrid nonlinear static-nonlinear
dynamic neural network models and addresses the challenges of optimal estimation of …

The development of an economic model predictive control (E-MPC) strategy is presented.
The strategy uses a novel dynamic flotation model that incorporates the physics of the froth …

We devise a novel technique to control the shape of polymer molecular weight distributions
(MWDs) in atom transfer radical polymerization (ATRP). This technique makes use of recent …

This paper has two objectives:(a) it describes the problem of finding a precise and
uncomplicated model of a neutralisation process,(b) it details development of a nonlinear …

Model predictive control (MPC) is one of the main process control techniques explored in the
recent past; it is the amalgamation of different technologies used to predict future control …

In this study, an efficient strategy for fault detection and isolation (FDI) of an Industrial Gas
Turbine is introduced based on ensemble learning methods. Four independent Wiener …

The use of inverse system model as a controller might be an efficient way in controlling non-
linear systems. It is also a known fact that fuzzy logic modeling is a powerful tool in …

pH neutralization process plants are widely used particularly in the wastewater treatment
and process industries such as biotechnology, chemical processing and pharmaceuticals …