%0 Journal Article
	%A J. Fernandez de Canete and  S. Gonzalez-Perez and  P. del Saz-Orozco
	%D 2008
	%J International Journal of Computer and Systems Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 23, 2008
	%T Software Tools for System Identification and Control using Neural Networks in Process Engineering
	%U https://publications.waset.org/pdf/278
	%V 23
	%X Neural networks offer an alternative approach both
for identification and control of nonlinear processes in process
engineering. The lack of software tools for the design of controllers
based on neural network models is particularly pronounced in this
field. SIMULINK is properly a widely used graphical code
development environment which allows system-level developers to
perform rapid prototyping and testing. Such graphical based
programming environment involves block-based code development
and offers a more intuitive approach to modeling and control task in
a great variety of engineering disciplines. In this paper a
SIMULINK based Neural Tool has been developed for analysis and
design of multivariable neural based control systems. This tool has
been applied to the control of a high purity distillation column
including non linear hydrodynamic effects. The proposed control
scheme offers an optimal response for both theoretical and practical
challenges posed in process control task, in particular when both,
the quality improvement of distillation products and the operation
efficiency in economical terms are considered.
	%P 3657 - 3661