NDLI: Decoupling the identification of linear and nonlinear parts in block-oriented nonlinear models using subspace identification approach

Content Provider	IEEE Xplore Digital Library
Author	Jeng, Jyh-Cheng Liu, Chia-Hung
Copyright Year	2011
Description	Author affiliation: Department of Chemical Engineering and Biotechnology National Taipei University of Technology, Taipei, Taiwan (Jeng, Jyh-Cheng; Liu, Chia-Hung)
Abstract	In this paper, novel noniterative algorithms for the identification of (multivariable) block-oriented nonlinear models (Hammerstein and Wiener models), consisting of a cascade combination of a linear dynamic block and a nonlinear static one, are presented. The proposed algorithms enable the identifications of the nonlinear and linear blocks fully separated without any special design for input test signals. Therefore, both the experimental and computational complexities during the identification procedures can be significantly reduced. The proposed method represents the linear dynamics as finite impulse response (FIR) model and approximates the static nonlinearity by expansions of basis functions. The key identification algorithms are derived from the subspace identification method. Simulation examples demonstrate that the proposed identification method is valid.
Starting Page	1920
Ending Page	1925
File Size	484672
Page Count	6
File Format	PDF
ISBN	9781457707148
e-ISBN	9784907764395
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-13
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	SICE (The Society of Instrument and Cont
Subject Keyword	Finite impulse response filter Mathematical model Biological system modeling Adaptation models Estimation Algorithm design and analysis Finite element methods Process control Block-oriented nonlinear models Nonlinear identification Subspace identification method
Content Type	Text
Resource Type	Article

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