| 1. |
- Abrahamsson, Tomas, et al.
(författare)
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A Study of some Approaches to Vibration Data Analysis
- 1993
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Using data from extensive vibrational tests of the new aircraft Saab 2000 three different methods for vibration analysis are studied. These methods are ERA (eigensystem realization algorithm), N4SID (a subspace method) and PEM (prediction error approach). We find that both the ERA and N4SID methods give good initial model parameter estimates that can be further improved by the use of PEM. We also find that all methods give good insights into the vibrational modes.
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| 2. |
- Akçay, Hüseyin, et al.
(författare)
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On the Choice of Norms in System Identification
- 1994
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Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 103-108
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).
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| 3. |
- Andersson, Peter, et al.
(författare)
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A Test Case for Adaptive Control : Car Steering
- 1981
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Ingår i: Proceedings of the 1981 IFAC Symposium on Theory and Applications of Digital Control. - Linköping : Linköping University. - 9780080276182
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Rapport (övrigt vetenskapligt/konstnärligt)
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| 4. |
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| 5. |
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| 6. |
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| 7. |
- Fnaiech, Farhat, et al.
(författare)
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Recursive Identification of Bilinear Systems
- 1985
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Methods of identifying bilinear systems from recorded input-output data are discussed in this article. A short survey of the existing literature on the topic is given. ‘Standard’ methods from linear systems identification, such as least squares, extended least squares, recursive prediction error and instrumental variable methods are transferred to bilinear, input-output model structures and tested in simulation. Special attention is paid to problems of stabilizing the model predictor, and it is shown how a time-varying Kalman filter and associated parameter estimation algorithm can deal with this problem.
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| 8. |
- Forsman, Krister, et al.
(författare)
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On the Dead-Zone in System Identification
- 1991
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Ingår i: Proceedings of the 9th IFAC Symposium on System Identification and System Parameter Estimation. - Linköping : Linköping University. ; , s. 1410-1414
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A prediction error method for parameter estimation in a dynamical system is studied.The following problems are treated in this paper:When is the DZ estimate inconsistent, and what is the set of parameters which minimizes the criterion in the case of inconsistency?What happens to the variance of the estimate as the DZ is introduced?Does the deadzone give a better estimate than LS when there are unmodelled deterministic disturbances present?What are the relations between identification with a deadzone criterion and so called set membership identification?
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| 9. |
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| 10. |
- Friedlander, Benjamin, et al.
(författare)
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Lattice Implementation of the Recursive Maximum Likelihood Algorithm
- 1981
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Ingår i: Proceedings of the 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes. - Linköping : Linköping University. ; , s. 1083-1084
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A lattice implementation of the extended least-squares algorithm was recently developed. The convergence of that algorithm depends on a positive real condition, a fact which limits its usefulness in some applications. In this note the lattice equivalent of the recursive maximum likelihood algorithm is derived. This technique does not require the positive real condition and is suitable for modeling and prediction of general ARMA time-series.
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