DocumentCode :
184027
Title :
A finite element based method for identification of switched linear systems
Author :
Sefidmazgi, Mohammad Gorji ; Moradi Kordmahalleh, Mina ; Homaifar, Abdollah ; Karimoddini, Ali
Author_Institution :
Electr. Eng. Dept., North Carolina A&T State Univ., Greensboro, NC, USA
fYear :
2014
fDate :
4-6 June 2014
Firstpage :
2644
Lastpage :
2649
Abstract :
Non-stationary time series analysis is important in the study of complex systems. Finding mathematical models for such complex systems with transitions between different phases is an ill-posed problem. This paper brings the problem of time series analysis into the context of hybrid modeling. Approximating the hybrid system by a switched linear system, the problem is reduced to identifying the switching times and model parameters. To address this problem, the non-stationary time series clustering technique based on Finite Elements is used for modeling of switched linear systems. The advantage of this method is that it is not necessary to add restrictive statistical assumptions on system variables. Illustrative examples have been provided to verify the proposed algorithm.
Keywords :
approximation theory; finite element analysis; identification; large-scale systems; linear systems; pattern clustering; time series; complex systems; finite element based method; hybrid modeling; hybrid system approximation; ill-posed problem; mathematical models; model parameter identification; nonstationary time series analysis; nonstationary time series clustering technique; restrictive statistical assumptions; switched linear system identification; switched linear system modeling; switching time identification; Finite element analysis; Hidden Markov models; Linear systems; Mathematical model; Optimization; Switches; Time series analysis; Computational methods; Modeling and simulation; Switched systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
ISSN :
0743-1619
Print_ISBN :
978-1-4799-3272-6
Type :
conf
DOI :
10.1109/ACC.2014.6858898
Filename :
6858898
Link To Document :
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