Paper Info
Title
Soft Computing Testing in Real Industrial Platforms for Process Intelligent Control
Abstract
By testing advanced control techniques based on Soft Computing into industrial platforms is possible to analyse the feasibility and reliability of these implementations for being subsequently used in real industrial processes. In many cases, this fact is not taken into account for several reasons concerning with the complexity of performing hardware implementations. Hence, simulation testing becomes the last step before showing an implemented solution. The main objective of this work is to give a step beyond for achieving a more realistic test of the Intelligent Control techniques. For this reason, a first approximation of a Genetic Algorithm controller (NSGA-II) is implemented, tested, studied and compared in the stages of the controller design, and simultaneously in different industrial platforms. Most relevant results obtained in software simulation and in Hardware In the Loop (HIL) implementation are finally shown and analysed.
Year
DOI
Venue
2012
10.1007/978-3-642-32922-7_23
SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS
Field
DocType
Volume
Intelligent control,Control theory,Controller design,Computer science,Model predictive control,Implementation,Theoretical computer science,Hardware-in-the-loop simulation,Soft computing,Genetic algorithm,Embedded system
Conference
188
ISSN
Citations 
PageRank 
2194-5357
2
0.37
References 
Authors
12
5
Name
Order
Citations
PageRank
Ekaitz Larzabal120.71
J. A. Cubillos220.37
Mikel Larrea-Sukia320.71
Eloy Irigoyen43814.23
Juan José Valera García5161.85