Title
A robust global approach for LPV FIR model identification with time-varying time delays.
Abstract
Robust identification of the linear parameter varying (LPV) finite impulse response (FIR) model with time-varying time delays is considered in this paper. A robust observation model based on Laplace distribution is established to deal with the output data contaminated with the outliers, which are commonly existed in modern industries. A Markov chain model is utilized to model the correlation between the time delays as they do not simply change randomly in reality. A transition probability matrix and an initial probability distribution vector are used to govern the switching mechanism of the time delays. Since it is difficult to optimize the complex log likelihood function directly, the derivations of the proposed algorithm are performed under the framework of Expectation-Maximization (EM) algorithm. A numerical example and a chemical process are utilized to verify the effectiveness of the proposed approach.
Year
DOI
Venue
2018
10.1016/j.jfranklin.2018.07.025
Journal of the Franklin Institute
Field
DocType
Volume
Complex logarithm,Likelihood function,Stochastic matrix,Laplace distribution,Control theory,Markov chain,Outlier,Probability distribution,Finite impulse response,Mathematics
Journal
355
Issue
ISSN
Citations 
15
0016-0032
0
PageRank 
References 
Authors
0.34
15
3
Name
Order
Citations
PageRank
Xin Liu124438.07
xianqiang yang25910.79
Weili Xiong3285.92