DocumentCode
155942
Title
Process identification using Hammerstein model with gradient descent algorithm
Author
Chakraborty, Arpan ; Patra, Sankar Narayan
Author_Institution
Appl. Electron. & Instrum. Dept., Univ. Inst. of Technol., Burdwan, India
fYear
2014
fDate
Jan. 31 2014-Feb. 2 2014
Firstpage
738
Lastpage
742
Abstract
The paper demonstrates a method for process optimization with the help of a Hammerstein Model hybridized with Gradient Descent Algorithm (for the minimization of error). This involves determination of the local minimum of error function and thus provides the corrective adjustments to the Hammerstein model parameters for the foresaid optimization.
Keywords
gradient methods; identification; minimisation; nonlinear systems; Hammerstein model; error minimization; gradient descent algorithm; process identification; process optimization; Algorithm design and analysis; Biological system modeling; Convergence; Instruments; Iterative methods; Mathematical model; Optimization; Artificial Neural Network (ANN); Gradient Descent Algorithm (GDA); Hammerstein Model; LTI System; Process Identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Instrumentation, Energy and Communication (CIEC), 2014 International Conference on
Conference_Location
Calcutta
Type
conf
DOI
10.1109/CIEC.2014.6959188
Filename
6959188
Link To Document