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- Zhen-Dong, Yuan, et al.
(author)
-
Optimal Input Design by Frequency Domain Criteria
- 1982
-
In: Proceedings of the 21st IEEE Conference on Decision and Control. - Linköping : Linköping University. ; , s. 1005-1006
-
Reports (other academic/artistic)abstract
- Some explicit, analytical result on optimal input design for identification of transfer functions are derived. The results are asymptotic as the model order increases. This can be interpreted as a reduction of prejudice in the design; the prejudice being that the system is "known" to belong to a certain low-order model set.
|
|
| 32. |
- Fnaiech, Farhat, et al.
(author)
-
Recursive Identification of Bilinear Systems
- 1985
-
Reports (other academic/artistic)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.
|
|
| 33. |
- Fnaiech, Farhat, et al.
(author)
-
Recursive Identification of Bilinear Systems
- 1987
-
In: International Journal of Control. - : Taylor & Francis. - 0020-7179 .- 1366-5820. ; 45:2, s. 453-470
-
Journal article (peer-reviewed)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.
|
|
| 34. |
- Gevers, Michel, et al.
(author)
-
Benefits of Feedback in Experiment Design
- 1985
-
In: Proceedings of the 7th IFAC Symposium on Identification and System Parameter Estimation. - : Pergamon Press. ; , s. 909-914
-
Conference paper (peer-reviewed)
|
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| 35. |
|
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| 36. |
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| 37. |
- Gevers, Michel, et al.
(author)
-
Optimal Experimental Designs with Respect to the Intended Model Application
- 1986
-
In: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 22:5, s. 543-554
-
Journal article (peer-reviewed)abstract
- The purpose of the design of identification experiments is to make the collected data maximally informative with respect to the intended use of the model, subject to constraints that might be at hand. When the true system is replaced by an estimated model, there results a performance degradation that is due to the error in the transfer function estimates. Using some recent asymptotic expressions for the bias and the variance of the estimated transfer function, it is shown how this performance degradation can be minimized by a proper experiment design. Several applications, where it is beneficial to let the experiment be carried out in closed loop, are highlighted.
|
|
| 38. |
- Gevers, Michel, et al.
(author)
-
Optimal Experimental Designs with Respect to the Intended Model Application
- 1985
-
Reports (other academic/artistic)abstract
- The purpose of the design of identification experiments is to make the collected data maximally informative with respect to the intended use of the model, subject to constraints that might be at hand. When the true system is replaced by an estimated model, there results a performance degradation that is due to the error in the transfer function estimates. Using some recent asymptotic expressions for the bias and the variance of the estimated transfer function, it is shown how this performance degradation can be minimized by a proper experiment design. Several applications, where it is beneficial to let the experiment be carried out in closed loop, are highlighted.
|
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| 39. |
|
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| 40. |
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