TY - JOUR
T1 - System identification and control of pressure process rig® system using backpropagation neural networks
AU - Putro, Benyamin Kusumo
AU - Priandana, Karlisa
AU - Wahab, Wahidin
N1 - Publisher Copyright:
© 2006-2015 Asian Research Publishing Network (ARPN).
PY - 2015/11/18
Y1 - 2015/11/18
N2 - A neural networks based direct inverse controller for Pressure Process Rig® system is presented, including with the performance analysis using an open-loop and a closed loop system. In order to enhance the performance characteristics of this direct inverse controller, a Fine-Tuning method is proposed. Experimental results show that the open-loop system shows lower MSE compare with that of the closed-loop system, and the Fine-Tuned NN-DIC method always performed better with lower MSE compare with that of the normal NN-DIC method.
AB - A neural networks based direct inverse controller for Pressure Process Rig® system is presented, including with the performance analysis using an open-loop and a closed loop system. In order to enhance the performance characteristics of this direct inverse controller, a Fine-Tuning method is proposed. Experimental results show that the open-loop system shows lower MSE compare with that of the closed-loop system, and the Fine-Tuned NN-DIC method always performed better with lower MSE compare with that of the normal NN-DIC method.
KW - Back propagation learning
KW - Direct inverse controller
KW - Fine-tuned DIC method
KW - Neural networks
UR - http://www.scopus.com/inward/record.url?scp=84947053118&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84947053118
SN - 1819-6608
VL - 10
SP - 7190
EP - 7195
JO - ARPN Journal of Engineering and Applied Sciences
JF - ARPN Journal of Engineering and Applied Sciences
IS - 16
ER -