Production scheduling and process control have the common aim of identifying
(economically) optimal operational decisions, and it is reasonable to expect that significant …

The measurement and control of polymerization reactors is very challenging due to the
complexity of the physical mechanisms and polymerization kinetics. In these reactors many …

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 …

A nonlinear controller synthesis scheme is presented that retains the original spirit and
characteristics of conventional (linear) model predictive control (MPC) while extending its …

In this paper, we propose a novel framework for integrating scheduling and nonlinear control
of continuous processes. We introduce the time scale-bridging model (SBM) as an explicit …

Two formulations of a nonlinear model predictive control scheme based on the second-order
Volterra series model are presented. The first formulation determines the control action …

In the present article, recent developments on modeling and optimization of particulate
polymerization processes are reviewed. A unified population balance approach is described …

This paper concerns general MIMO nonlinear processes, whose dynamic behavior is
described by a standard state‐space model of arbitrary order, including measurable …

Discrete‐time Volterra models are widely used in various application areas. Their
usefulness is mainly because of their ability to approximate to an arbitrary precision any …

A technique for predicting polymer quality in batch polymerisation reactors using robust
neural networks is proposed in this paper. Robust neural networks are used to learn the …