Title
Identification of linear parameter varying system with dual-rate sampled data and uncertain measurement delay
Abstract
The parameter estimation for linear parameter varying (LPV) system with dual-rate sampled data in presence of unknown measurement delays is considered in this paper. The local identification approach is adopted and the global LPV model is constructed by synthesizing several local models by using the probability functions. The identification problem is formulated in the scheme of expectation-maximization (EM) algorithm and dual-rate sampled data, random measurement delays, and parameter varying property of the system are handled simultaneously. The iterative formulas to estimate the model parameters, measurement delays, and unknown parameters in probability functions based on dual-rate sampled data are derived. One simulation example is employed to demonstrate the effectiveness of the proposed method.
Year
DOI
Venue
2016
10.1109/ISIE.2016.7744872
2016 IEEE 25th International Symposium on Industrial Electronics (ISIE)
Keywords
Field
DocType
linear parameter varying system identification,dual-rate sampled data,uncertain measurement delay,global LPV model,unknown measurement delays,probability functions,expectation-maximization algorithm,EM,random measurement delays,system parameter varying property,iterative formulas
Data modeling,Job shop scheduling,Control theory,Measurement delay,Control engineering,Estimation theory,Mathematics,Parameter identification problem
Conference
ISSN
ISBN
Citations 
2163-5137
978-1-5090-0874-2
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
xianqiang yang15910.79
Hao Sun24418.15
Lifei Bai341.46
Xin Liu428774.92