| 1. |
- Akçay, Hüseyin, et al.
(author)
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On the Choice of Norms in System Identification
- 1994
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In: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 103-108
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Reports (other academic/artistic)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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| 2. |
- Ljung, Lennart, 1946-, et al.
(author)
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Adaptation and Tracking in System Identification
- 1988
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In: Proceedings of the 8th IFAC Symposium on Identification and System Parameter Estimation. - Linköping : Linköping University. ; , s. 1-10
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Reports (other academic/artistic)abstract
- This article gives a survey of basic techniques to derive and analyse algorithms for tracking time-varying systems. Special attention is paid to how different assumptions about the true system affect the algorithms. Explicit and semi-explicit expressions for the means square errors are derived, which clearly demonstrate the character of the trade-off between tracking ability and noise sensitivity.
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| 3. |
- Ljung, Lennart, 1946-
(author)
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On the Estimation of Transfer Functions
- 1987
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In: Proceedings of the 10th IFAC World Congress on Automatic Control. - Linköping : Linköping University. - 9780080357287 ; , s. 271-281
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Reports (other academic/artistic)
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| 4. |
- Ljung, Lennart, 1946-
(author)
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Recursive Identification Techniques
- 1982
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In: Proceedings of the 1982 IEEE International Conference on Acoustics, Speech and Signal Processing. - Linköping : Linköping University. ; , s. 627-630
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Reports (other academic/artistic)abstract
- Some basic results on recursive identification techniques and their properties are reviewed. The link between adaptive algorithms, recursive identification, and off-line identification is stressed. The fundamental character of the prediction and its gradient with respect to the adjustable parameters is pointed out.
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| 5. |
- Ottersten, Björn, et al.
(author)
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Asymptotic Results for Sensor Array Processing
- 1989
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In: Proceedings of the 1989 International Conference on Acoustics, Speech and Signal Processing. - Linköping : Linköping University. ; , s. 2266-2269
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Reports (other academic/artistic)abstract
- The emphasis of this study is on direction-of-arrival (DOA) estimation of narrowband emitter signals. There are two main signal models that have been used in the sensor array problem, namely, stochastic and deterministic. A discussion is presented of the models, their effect on the Cramer-Rao lower bounds (CRB), cases where the maximum likelihood (ML) estimator asymptotically achieves this bound, and how the bounds are related. It is shown that the asymptotic variance of the ML method based on the stochastic model is lower than that of the ML method based on the deterministic model. The stochastic ML variance and CRB are based on the assumption of Gaussian emitter signals, which can be an unrealistic assumption when narrowband signals are assumed. The authors show that the ML estimator based on the Gaussian signal model achieves the stochastic CRB asymptotically, regardless of the signal distribution. Numerical evaluations of the theoretical variances for different scenarios are presented to clarify the relationship between the methods and bounds discussed.
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| 6. |
- Stenman, Anders, et al.
(author)
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Just-in-Time Models for Dynamical Systems
- 1996
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In: Proceedings of Reglermöte 1996. - Linköping : Linköping University Electronic Press. ; , s. 285--289, s. 1115-1120 vol.1
-
Conference paper (other academic/artistic)abstract
- The concept of just in time models is introduced for models that are not estimated until they are really needed. The idea is to store all observations of the process in a database, and then estimate a local model at the current working point. The variance/bias tradeoff is optimized locally by adapting the number of data and their relative weighting. This is in contrast to general nonlinear black-box models, like neural networks, where the performance is optimized globally.
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| 7. |
- Trulsson, Eva, et al.
(author)
-
Stability in Adaptive Control by Persistently Exciting Regulators
- 1985
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In: Proceedings of the 24th IEEE Conference on Decision and Control. - Linköping : Linköping University. ; , s. 484-491
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Reports (other academic/artistic)abstract
- The stability of adaptive regulators, based on least-squares parameter estimation under arbitrary, bounded disturbances, is considered. Using an idea by Barabanov to obtain persistence of excitation a fairly simple and general stability result is obtained.
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| 8. |
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| 9. |
- Andersson, Peter, et al.
(author)
-
A Test Case for Adaptive Control : Car Steering
- 1981
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In: Proceedings of the 1981 IFAC Symposium on Theory and Applications of Digital Control. - Linköping : Linköping University. - 9780080276182
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Reports (other academic/artistic)
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| 10. |
- Björklund, Svante, et al.
(author)
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A Review of Time-Delay Estimation Techniques
- 2003
-
In: Proceedings of the 42nd IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780379241 ; , s. 2502-2507 vol.3
-
Reports (other academic/artistic)abstract
- This paper reviews and evaluates suggested methods for estimating the time-delay of linear systems in automatic control applications. A classification of the methods according to the underlying principles is suggested. The evaluation, done by analyzing the estimates of the methods from extensive simulated data in open loop, shows that different classes of methods have different properties and are suitable in different cases. Some method are clearly inferior to others. Recommendations are given on how to choose estimation method and input signal.
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