| 21. |
- Trulsson, Eva, et al.
(författare)
-
Stability in Adaptive Control by Persistently Exciting Regulators
- 1985
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Ingår i: Proceedings of the 24th IEEE Conference on Decision and Control. - Linköping : Linköping University. ; , s. 484-491
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Rapport (övrigt vetenskapligt/konstnärligt)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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| 22. |
- Viberg, Mats, et al.
(författare)
-
A statistical perspective on state-space modeling using subspace methods
- 1991
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Ingår i: Proceedings of the 30th IEEE Conference on Decision and Control. - Linköping : Linköping University. - 0780304500 ; , s. 1337-1342
-
Konferensbidrag (refereegranskat)abstract
- The authors investigate aspects of subspace-based state-space identification techniques from a statistical perspective. They concentrate their efforts on a simple approach which is based on finding the range-space of the observability matrix of a state-space representation. The system description is then found using the shift-invariance property of the observability matrix. It is shown that this results in a consistent system description for multivariable output-error models if the measurement noise is white in time and independent from output to output. The asymptotic covariance of the estimated poles of the system is also derived. In the test case studied, the subspace technique performs comparably with the statistically efficient PE (prediction error) method, whereas the IV (instrumental variable) method does notably worse. Hence, the subspace technique may be a strong candidate for determining initial values for the optimization in the efficient PE method.
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| 23. |
- Wahlberg, Bo, 1959-, et al.
(författare)
-
Design Variables for Bias Distribution in Transfer Function Estimation
- 1984
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Ingår i: Proceedings of the 23rd IEEE Conference on Decision and Control. - Linköping : Linköping University. ; , s. 335-341
-
Konferensbidrag (refereegranskat)abstract
- Estimation of transfer functions of linear systems is one of the most common system identification problems. Several different design variables, chosen by the user for the identification procedure, affect the properties of the resulting estimate. In this paper it is investigated how the choices of prefilters, noise models, sampling interval and prediction horizon (i.e. the use of k-step ahead prediction methods) influence the estimate. An important aspect is that the true system is not assumed to be exactly represented within the chosen model set. The estimate will thus be biased. It is shown how the distribution of bias in the frequency domain is governed by a weighting function, which emphasizes different frequency bands. The weighting function, in turn, is a result of the previously listed design variables. It is shown, e.g., that the common least squares method has a tendency to emphasize high frequencies, and that this can be counteracted by prefiltering.
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| 24. |
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| 25. |
- Ljung, Lennart, 1946-
(författare)
-
Teaching System Identification : Goals and Formats of Different Courses
- 2000
-
Ingår i: Proceedings of the 12th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 9780080435459
-
Konferensbidrag (refereegranskat)abstract
- Four cases of System Identification courses are discussed and described: A short introduction to participants without any prior knowledge, a course for industry, an undergraduate course and a graduate course.The discussion is carried out in terms of how to convey six basic messages to the course participants.
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| 26. |
- Akcay, H., et al.
(författare)
-
On the choice of norms in system identification
- 1996
-
Ingår i: IEEE Transactions on Automatic Control. - Linköping : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286. ; 41:9, s. 1367-1372
-
Tidskriftsartikel (refereegranskat)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). ©1996 IEEE.
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| 27. |
- Andersson, Peter, et al.
(författare)
-
A Test Case for Adaptive Control : Car Steering
- 1981
-
Ingår i: Proceedings of the 1981 IFAC Symposium on Theory and Applications of Digital Control. - Linköping : Linköping University. - 9780080276182
-
Rapport (övrigt vetenskapligt/konstnärligt)
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| 28. |
- Andersson, Torbjörn, et al.
(författare)
-
Identification Aspects of Inter-Sample Input Behavior
- 1994
-
Ingår i: Proceedings of the 10th IFAC Symposium on System Identification. - Linköping : Linköping University. - 9780080422251 ; , s. 137-142
-
Konferensbidrag (refereegranskat)abstract
- In this contribution aspects of inter-sample input signal behavior are examined. The starting point is that parametric identification always is performed on basis of discrete-time data. This is valid for identification of discrete-time models as well as continuous-time models. The usual assumptions on the input signal are; i) it is band-limited, ii) it is piecewise constant or iii) it is piecewise linear. One point made in this paper is that if a discrete-time model is used, the best possible (in the model structure) adjustment to data is made. This is independent of the assumption on the input signal. However, a transformation of the obtained discrete model to a continuous one is not possible without additional assumptions on the input signal. The other point made is that the frequency functions of the discrete models very well coincides with the frequency functions of the discretized continuous time models and the continuous time transfer function fitted in the frequency domain.
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| 29. |
- Björklund, Svante, et al.
(författare)
-
A Review of Time-Delay Estimation Techniques
- 2003
-
Ingår i: Proceedings of the 42nd IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780379241 ; , s. 2502-2507 vol.3
-
Rapport (övrigt vetenskapligt/konstnärligt)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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| 30. |
- Enqvist, Martin, 1976-, et al.
(författare)
-
Estimating Nonlinear Systems in a Neighborhood of LTI-approximants
- 2002
-
Ingår i: Proceedings of the 41st IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780375165 ; , s. 1005-1010 vol.1
-
Konferensbidrag (refereegranskat)abstract
- The estimation of Linear Time Invariant (LTI) models is a standard procedure in system identification. Any real-life system will however be nonlinear and time-varying, and the estimated model will converge to the LTI second order equivalent (LTI-SOE) of the true system. In this paper we consider some aspects of this convergence and the distance between the true system and its LTI-SOE. We show that there may be cases where even the slightest nonlinearity may cause big differences in the LTI-SOE. We also show a result that gives conditions that guarantee that the LTI-SOE is close to "the natural" LTI approximant. Finally, an upper bound on the distance between the LTI-SOE of a nonlinear FIR system with a white input signal and the linear part of the system is derived.
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