| 1. |
- Gunnarsson, Svante, 1959-, et al.
(författare)
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LQG Control of a Hydraulic Actuator with a Flexible Mechanical Load
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - Linköping : Linköping University. - 9780080422121 ; , s. 469-472
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a control system based on linear quadratic state feedback and state estimation for an hydraulic actuator with a flexible mechanical load. The purpose of the control system is to improve the dynamic properties by reducing the oscillatory behavior of the load and to eliminate the steady state error in the load position caused by external disturbances. Using a simplified linear model a control system is developed and evaluated using simulations and experiments.
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| 2. |
- Gustafsson, Fredrik, et al.
(författare)
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Identifiability in Blind Equalization
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - 9780080422121
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Konferensbidrag (refereegranskat)
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| 3. |
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| 4. |
- Hjalmarsson, Håkan, 1962-
(författare)
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A Model Variance Estimator
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - 9780080422121 ; , s. 5-10, s. 5-10
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Konferensbidrag (refereegranskat)
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| 5. |
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| 6. |
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| 7. |
- Lindskog, Peter, et al.
(författare)
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Applications of Kautz Models in System Identification
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - Linköping : Linköping University. - 9780080422121 ; , s. 309-312
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- FIR, ARX or AR model structures can be used to describe many industrial processes. Simple linear regression techniques can be applied to estimate such models from experimental data. However, for low signal to noise ratios in combination with transfer function poles and noise model zeros close to the unit circle, a large number of model parameters are needed to generate adequate models. The Kautz model structure generalizes FIR, ARX and AR models. By using a priori knowledge about the dominating time constants and damping factors of the system, the model complexity is reduced, and the linear regression structure is retained. The objective of this contribution is to study an industrial example, where Kautz models have distinct advantages. The data investigated corresponds to aircraft flight flutter, which is a state when an aircraft component starts to oscillate.
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| 8. |
- Ljung, Lennart, 1946-, et al.
(författare)
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On the Use of Regularization in System Identification
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - 9780080422121 ; , s. 381-386
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Konferensbidrag (refereegranskat)abstract
- Regularization is a standard statistical technique to deal with ill-conditioned parameter estimation problems. We discuss in this contribution what possibilities and advantages regularization offers in system identification. In the first place regularization reduces the variance error of a model, but at the same time it introduces a bias. The familiar trade-off between bias and variance error for the choice of model order/structure can therefore be discussed in terms of the regularization parameter. We also show how the well-known problem of parametrizing multivariable system can be dealt with using overparametrization plus regularization. A characteristic feature for this way of letting the parametrization/model structure/model order be solved by regularization is that it is an easy and "automatic" way of finding the important parameters and good parametrization. No statistical penalty is paid for the overparametrization, but there is a penalty of higher computational burden.
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| 9. |
- Ljung, Lennart, 1946-
(författare)
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The Process of Identification
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - 9780080422121 ; , s. 197-
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Konferensbidrag (refereegranskat)
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