A multi-layer feedforward neural network model based predictive control scheme is
developed for a multivariable nonlinear steel pickling process in this paper. In the acid baths …

This paper deals with the design and application of nonlinear model‐based control schemes
for stable and nonlinear benchmark industrial processes. The primary control objective is to …

In recent years, there has been a significant increase in the number of control system
techniques that are based on nonlinear concepts. One such method is the nonlinear inverse …

In a pharmaceutical industry, batch extractive distillation (BED), a combination process
between extraction and distillation processes, has been widely implemented to separate …

This work presents a novel control scheme based on approximating the inverse process
dynamics with a radial basis function (RBF) neural network model, trained with the fuzzy …

Tankless water heaters (TWHs) have been become more popular day-by-day in special
because of the low-power consumption that characterizes these devices in comparison with …

We explore the prospect for leveraging analogue electronic circuitry from lunar resources
and determine its utility for controlling production on the Moon. Since solid-state transistor …

An example embodiment may involve a machine learning model representing relationships
between a dependent variable and a plurality of n independent variables. The dependent …

This work addresses EKF and UKF tuning logic based PI Control algorithm implemented on
standard nonlinear process. A typical CSTR process was chosen to demonstrate the …

This paper describes neural network models for the prediction of the concentration profile of
a hydrochloric acid recovery process consisting of double fixed-bed ion exchange columns …