Identification algorithm for a class of nonlinear systems

Nonlinear system identification based on local model networks is considered for the nonlinear process where a nonlinear element is followed by linear dynamics. The local model is chosen as a linear model, or a simple block oriented nonlinear model, whose orders are determined through a criterion fun...

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Bibliographic Details
Published in2012 International Conference on Systems and Informatics (ICSAI2012) pp. 193 - 197
Main Authors Lianming Sun, Yuanming Ding, Yujin Yang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2012
Subjects
Adaptation models
Approximation methods
Computational modeling
local model
nonlinear system
Nonlinear systems
parameter estimation
Partitioning algorithms
system identification
Vectors
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Summary:Nonlinear system identification based on local model networks is considered for the nonlinear process where a nonlinear element is followed by linear dynamics. The local model is chosen as a linear model, or a simple block oriented nonlinear model, whose orders are determined through a criterion function with respect to both the approximation accuracy and model simplicity. The weight of every local model varies with the operating point of the present process state, and the parameters of local models are estimated through some simple parameter estimation algorithms. The algorithm can work even under the situation where little information on nonlinearity is available, and it can be implemented easily in practical systems. Moreover, its application to the processes with saturation and backlash is investigated to show the effective of the proposed algorithm.
ISBN:9781467301985
1467301981
DOI:10.1109/ICSAI.2012.6223436