Real-time Identification of the Draft System Using Neural Network

Making a good model is one of the most important aspects in the field of a control system. If one makes a good model, one is now ready to make a good controller for the system. The focus of this thesis lies on system modeling, the draft system in specific. In modeling for a draft system, one of the...

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Bibliographic Details
Published in:Fibers and polymers 2006-03, Vol.7 (1), p.62-65
Main Authors: Soon Yong Chun, Han Jo Bae, Seon Mi Kim, Moon W. Suh, P. Grady, Won Seok Lyoo, Won Sik Yoon, Sung Soo Han
Format: Article
Language:Korean
Subjects:
Control
Draft system
Modeling
Neural network
Sliver
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Summary:Making a good model is one of the most important aspects in the field of a control system. If one makes a good model, one is now ready to make a good controller for the system. The focus of this thesis lies on system modeling, the draft system in specific. In modeling for a draft system, one of the most common methods is the 'least-square method'; however, this method can only be applied to linear systems. For this reason, the draft system, which is non-linear and a time-varying system, needs a new method. This thesis proposes a new method (the MLS method) and demonstrates a possible way of modeling even though a system has input noise and system noise. This thesis proved the adaptability and convergence of the MLS method.
ISSN:1229-9197
1875-0052