Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
Online ISSN : 2188-4749
Print ISSN : 2188-4730
第42回ISCIE「確率システム理論と応用」国際シンポジウム(2010年11月, 岡山)
Identification of Partially Unknown System Matrix From Noisy Observation Data via Pseudomeasurement Approach
KENTARO KAMEYAMAAKIRA OHSUMI
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2011 年 2011 巻 p. 27-32

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In this paper, an identification method of the state-space model is proposed. Proposed method assumes that some entries of system matrix A is unknown and identify these entries from input and output data. The key idea of the proposed method is the use of pseudomeasurement which is fictitiously constructed data as if it were made on the unknown entries. Augmenting this pseudomeasurement with original observation data, unknown entries (and state-vector) are identified by the extended Kalman filter.
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© 2011 ISCIE Symposium on Stochastic Systems Theory and Its Applications
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