This is a detailed review on olefin polymerization models, and the most recent process
control approaches used to control these nonlinear systems are presented. Great focus has …

The aim of this paper is to develop a type-1 and a type-2 fuzzy logic PID controller (type-1
FLC and type-2 FLC, respectively) for the control of a binary distillation column, the …

The nonlinear model predictive control (NMPC) is an on-line application based on nonlinear
convolution models. It is an appealing control methodology, but it is difficult to implement …

In this study, an inverse controller based on a type-2 fuzzy model control design strategy is
introduced and this main controller is embedded within an internal model control structure …

This paper presents a model-based approach for on-line monitoring of difficult-to-measure
quality variables with the description of their dynamic behavior. The strategy comprises the …

Whether flow dynamics in a novel circulating-turbulent fluidized bed (C-TFB) belongs to a
new flow regime or just a transition state is controversial. In order to resolve this confusion …

Typically chemical processes have significant nonlinear dynamics, but despite this, industry
is conventionally still using PID-based regulatory control systems. Moreover, process units …

The quality control and optimization of Simulated Moving Bed processes are still a
challenge. Among the main reasons for that, the real time measurement of its main …

The complex flows under high gravity in intricate advanced oxidation reactions expose a
high-gravity advanced oxidation process (HiGee-AOP) modeling and control to uncertainty …

Model predictive control (MPC) is an online application based on dynamic models. Its
application faces two major obstacles:(i) computational constraints and (ii) the need to …