DocumentCode :
114653
Title :
Interval system identification for MIMO ARX models of minimal order
Author :
Zaiser, Stefan ; Buchholz, Michael ; Dietmayer, Klaus
Author_Institution :
Inst. of Meas., Control & Microtechnol., Ulm Univ., Ulm, Germany
fYear :
2014
fDate :
15-17 Dec. 2014
Firstpage :
1774
Lastpage :
1779
Abstract :
Focus of this paper is on system identification of models in AutoRegressive with eXogenous inputs form from data with unknown, but bounded measurement errors. Hereby, these errors in data as well as the resulting uncertainty in parameters are represented by intervals. The proposed method can be applied to linear, time invariant systems with multiple inputs and multiple outputs. The main contribution are algorithms to determine the minimal order of a discrete-time model description in ARX form with interval parameters. In addition, an approach for using multiple sequences of measurement data is introduced. Finally, the method is demonstrated and discussed on a simulation example.
Keywords :
MIMO systems; autoregressive processes; discrete time systems; identification; linear systems; autoregressive-with-exogenous inputs; bounded measurement errors; discrete-time model description; interval parameters; interval system identification; linear systems; minimal order MIMO ARX models; multiple inputs-and-multiple outputs; multiple measurement data sequences; time invariant systems; Computational modeling; Data models; Delays; MIMO; Mathematical model; Measurement errors; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-1-4799-7746-8
Type :
conf
DOI :
10.1109/CDC.2014.7039655
Filename :
7039655
Link To Document :
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