PCA based pressure control of a gas mixing chamber

Authors:
J. M. Escaño;F. Dorado;C. Bordons
Affiliations:
Department of System Engineering and Automation, University of Seville, Spain;Department of System Engineering and Automation, University of Seville, Spain;Department of System Engineering and Automation, University of Seville, Spain
Venue:
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Year:
2009

Citing 5
Cited 0

Generalized predictive control—Part I. The basic algorithm

Automatica (Journal of IFAC)
Model Predictive Control in the Process Industry

Model Predictive Control in the Process Industry
Fuzzy model-based control of complex plants

IEEE Transactions on Fuzzy Systems
Identification and control of dynamic systems using recurrent fuzzy neural networks

IEEE Transactions on Fuzzy Systems
Diagonal recurrent neural networks for dynamic systems control

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

PCA is a popular technique used in model reduction and fault diagnosis and isolation. In this work PCA is used to reduce the dimensionality of a MISO system. The coupling among the variables and the process output is taken into account through the projection into the PCA axis. The technique is applied to a gas mixing chamber in a Copper smelter factory, whose nonlinear behavior and large number of variables involved justify this approach. The control strategy is defined therefore in a straight and simple way making use of this new virtual and reduced system. The controller is simulated using a neurofuzzy model of the process that has been obtained using real data form the plant.