Conference proceeding
Simultaneous State Observability and Parameters Identifiability of Discrete Stochastic Linear Systems
1993 American Control Conference, pp 1231-1235
Jun 1993
Abstract
A new representation of discrete stochastic linear time-invariant systems is presented. This representation generalizes in a rigorous way the concept of observability to parameters identifiability. The state of the augmented system is a combination of the state of the orginal system and the unknown parameters. It is shown that simultaneous state observability and parameters identifiability of linear time-invariant system is an observability problem of an augmented linear time-variant system. It is shown that the well known results derived by Least Squares(LS) algorithms evolve as a special case of the new representation. The representation yields necessary and sufficient conditions on the simultaneous state observability and parameters identifiability. Sufficient conditions derived from the necessary and sufficient conditions are weaker than the well known persistent excitation conditions in the existing least squares schemes. These conditions apply to estimation in open and closed loop without further restrictions. This reestablishes the well known results for identification in closed loop. The observability analysis enables generalization of similar results for nonlinear time-varying feedback. Simulation results demonstrate the performance of estimation with this new approach.
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10 citations in Scopus
Details
- Title
- Simultaneous State Observability and Parameters Identifiability of Discrete Stochastic Linear Systems
- Creators
- Ilan Rusnak - Drexel UniversityAllon Guez - Drexel UniversityIzhak Bar-Kana - Drexel UniversityAMER AUTOMAT CONTROL COUNCIL
- Publication Details
- 1993 American Control Conference, pp 1231-1235
- Conference
- 1993 American Control Conference (San Francisco, California, United States, 02 Jun 1993–04 Jun 1993)
- Publisher
- IEEE
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:A1993BY87D00276
- Scopus ID
- 2-s2.0-0027803536
- Other Identifier
- 991019182776704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Electrical & Electronic