The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for
operations management with the aim of finding solutions to problems that are increasing in …

In the Proportional-Integral-Derivative (PID) controllers the control signal is a linear function
of: the current control error (the proportional part), the past errors (the integral part) and the …

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 …

Abstracts A submerged combustion vaporizer (SCV) is normally used at a liquefied natural
gas (LNG) terminal to vaporize LNG and supply natural gas to domestic and industrial …

This paper presents new results on a neural network approach to nonlinear model predictive
control. At first, a nonlinear system with unmodeled dynamics is decomposed by means of …

Learning-based controllers, and especially learning-based model predictive controllers,
have been used for a number of different applications with great success. In spite of good …

This paper details nonlinear Model-based Predictive Control (MPC) algorithms for MIMO
processes modelled by means of neural networks of a feedforward structure. Two general …

In the last three decades, artificial intelligence (AI) has been increasingly and vigorously
utilized for process control in chemical, biochemical, and biomedical engineering. These …

Assessing controller performance in normal operation needs reproducible conditions and
comparison with the best possible result. Tests in emulation are reproducible. Model …

This paper is concerned with using artificial neural networks for modelling and temperature
control of a yeast fermentation biochemical reactor. At first, a neural model of the process is …