Much has been written about the general difficulty of developing the models required for
model-based control of processes whose dynamics exhibit signif icant nonlinearity (for …

In recent years, much attention has been focused upon predictive control of nonlinear
systems. The implementation of such a control strategy for real processes has greatly …

There is a large demand to apply nonlinear algorithms to control nonlinear systems. With
algorithms considering the process nonlinearities, better control performance is expected in …

This paper presents a new contribution in the implementation of Volterra model predictive
control for fast dynamics systems. The control approaches considered results on a switch …

Neural networks can be considered to be new modelling tools in process control and
especially in non-linear dynamical systems cases. Their ability to approximate non-linear …

Much has been written about the general difficulty of developing the models required for
model-based control of processes whose dynamics exhibit signif icant nonlinearity (for …

In this paper we present a new nonlinear predictive control strategy based on Volterra
model. In the objective of minimizing the computation time by avoiding non-linear …

This paper presents the identification and the control of a semi-batch reactor. The process is
described by a parametric Volterra model. The control strategy uses a nonlinear model …

Purpose–The paper aims to present a new concept based on a multi‐agent approach in the
area of nonlinear model predictive control (MPC) for fast systems. Design/methodology …

1.1 Background Technology development is constantly bringing more complex production
facilities and thus raises the need of appropriate tool for engineers to help them understand …