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- Ljung, Lennart, 1946-, et al.
(författare)
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Closed-Loop Subspace Identification with Innovation Estimation
- 2003
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Ingår i: Proceedings of the 13th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 9780080437095 ; , s. 887-892
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Konferensbidrag (refereegranskat)abstract
- Most subspace identication algorithms are not applicable to closed-loop identication because they require future input to be uncorrelated with pastinnovation. In this paper, we propose a new subspace identication method that remove this requirement by using a parsimonious model formulation with innovation estimation. A simulation example is included to show the effectiveness of the proposed method.
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- Ljung, Lennart, 1946-, et al.
(författare)
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On Consistency of Closed-Loop Subspace Identification with Innovation Estimation
- 2004
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Ingår i: Proceedings of the 43rd IEEE Conference on Decision and Control. - 0780386825 ; , s. 2195-2200
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Konferensbidrag (refereegranskat)abstract
- In this paper, we show that the consistency of closed-loop subspace identification methods (SIMs) can be achieved through innovation estimation. Based on this analysis, a sufficient condition for the consistency of a new proposed closed-loop SIM is given, A consistent estimate of the Kalman gain under closed-loop conditions is also provided based on the algorithm. A multi-input-multi-output simulation shows that itis consistent under closed-loop conditions, when traditional SIMs fail to provide consistent estimates.
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- Ljung, Lennart, 1946-, et al.
(författare)
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Parallel QR Implementation of Subspace Identification with Parsimonious Models
- 2003
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Ingår i: Proceedings of the 13th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 9780080437095 ; , s. 1631-1636
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Konferensbidrag (refereegranskat)abstract
- In this paper we reveal that the typical subspace identification algorithms use non-parsimonious model formulations, with extra terms in the model that appear to be non-causal. These terms are the causes for inflated variance in the estimates and partially responsible for the loss of closed-loop identifiability. We then propose a parallel parsimonious formulation of a new subspace identification algorithm and demonstrate the effectiveness of the proposed algorithm via simulation.
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