TY - JFULL AU - J. Fernandez de Canete and S. Gonzalez-Perez and P. del Saz-Orozco PY - 2008/12/ TI - Software Tools for System Identification and Control using Neural Networks in Process Engineering T2 - International Journal of Computer and Systems Engineering SP - 3656 EP - 3661 VL - 2 SN - 1307-6892 UR - https://publications.waset.org/pdf/278 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 23, 2008 N2 - 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. ER -