| 1. |
- Goodwin, Graham C., et al.
(författare)
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Robust Identification of Process Models from Plant Data
- 2008
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Ingår i: Journal of Process Control. - : Elsevier. - 0959-1524. ; 18:9, s. 810-820
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Tidskriftsartikel (refereegranskat)abstract
- A precursor to any advanced control solution is the step of obtaining an accurate model of the process. Suitable models can be obtained from phenomenological reasoning, analysis of plant data or a combination of both. Here, we will focus on the problem of estimating (or calibrating) models from plant data. A key goal is to achieve robust identification. By robust we mean that small errors in the hypotheses should lead to small errors in the estimated models. We argue that, in some circumstances, it is essential that special precautions, including discarding some part of the data, be taken to ensure that robustness is preserved. We present several practical case studies to illustrate the results.
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| 2. |
- Swift, Imogen J, et al.
(författare)
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A systematic review of progranulin concentrations in biofluids in over 7,000 people-assessing the pathogenicity of GRN mutations and other influencing factors.
- 2024
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Ingår i: Alzheimer's Research & Therapy. - 1758-9193. ; 16:1
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Tidskriftsartikel (refereegranskat)abstract
- Pathogenic heterozygous mutations in the progranulin gene (GRN) are a key cause of frontotemporal dementia (FTD), leading to significantly reduced biofluid concentrations of the progranulin protein (PGRN). This has led to a number of ongoing therapeutic trials aiming to treat this form of FTD by increasing PGRN levels in mutation carriers. However, we currently lack a complete understanding of factors that affect PGRN levels and potential variation in measurement methods. Here, we aimed to address this gap in knowledge by systematically reviewing published literature on biofluid PGRN concentrations.Published data including biofluid PGRN concentration, age, sex, diagnosis and GRN mutation were collected for 7071 individuals from 75 publications. The majority of analyses (72%) had focused on plasma PGRN concentrations, with many of these (56%) measured with a single assay type (Adipogen) and so the influence of mutation type, age at onset, sex, and diagnosis were investigated in this subset of the data.We established a plasma PGRN concentration cut-off between pathogenic mutation carriers and non-carriers of 74.8ng/mL using the Adipogen assay based on 3301 individuals, with a CSF concentration cut-off of 3.43ng/mL. Plasma PGRN concentration varied by GRN mutation type as well as by clinical diagnosis in those without a GRN mutation. Plasma PGRN concentration was significantly higher in women than men in GRN mutation carriers (p=0.007) with a trend in non-carriers (p=0.062), and there was a significant but weak positive correlation with age in both GRN mutation carriers and non-carriers. No significant association was seen with weight or with TMEM106B rs1990622 genotype. However, higher plasma PGRN levels were seen in those with the GRN rs5848 CC genotype in both GRN mutation carriers and non-carriers.These results further support the usefulness of PGRN concentration for the identification of the large majority of pathogenic mutations in the GRN gene. Furthermore, these results highlight the importance of considering additional factors, such as mutation type, sex and age when interpreting PGRN concentrations. This will be particularly important as we enter the era of trials for progranulin-associated FTD.
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| 3. |
- Agüero, Juan C., et al.
(författare)
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Accuracy of linear multiple-input multiple-output (MIMO) models obtained by maximum likelihood estimation
- 2012
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 48:4, s. 632-637
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we study the accuracy of linear multiple-input multiple-output (MIMO) models obtained by maximum likelihood estimation. We present a frequency-domain representation for the information matrix for general linear MIMO models. We show that the variance of estimated parametric models for linear MIMO systems satisfies a fundamental integral trade-off. This trade-off is expressed as a multivariable 'water-bed' effect. An extension to spectral estimation is also discussed.
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| 4. |
- Agüero, Juan C., et al.
(författare)
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Fundamental Limitations on the Accuracy of MIMO Linear Models Obtained by PEM for Systems Operating in Open Loop
- 2009
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Ingår i: Proceedings of the Joint 48th IEEE Conference on Decision and Control (CDC’09) and 28th Chinese Control Conference (CCC’09). - 9781424438716 ; , s. 482-487
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Konferensbidrag (refereegranskat)abstract
- In this paper we show that the variance of estimated parametric models for open loopMultiple-Input Multiple-Output (MIMO) systems obtained by the prediction error method (PEM) satisfies a fundamental integral limitation. The fundamental limitation gives rise to a multivariable 'water-bed' effect.
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| 5. |
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| 6. |
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| 7. |
- Cassasco, Diego S., et al.
(författare)
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On the Accuracy of Parameter Estimation for Continuous Time Nonlinear Systems from Sampled Data
- 2011
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Ingår i: Proceedings of the 50th IEEE Conference on Decision and Control. - 9781612847993 - 9781612848006 ; , s. 4308-4311
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Konferensbidrag (refereegranskat)abstract
- This paper deals with the issue of estimating the parameters in a continuous-time nonlinear dynamical model from sampled data. We focus on the issue of bias-variance trade-offs. In particular, we show that the bias error can be significantly reduced by using a particular form of sampled data model based on truncated Taylor series. This model retains the conceptual simplicity of models based on Euler integration but has much improved accuracy as a function of the sampled period.
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| 8. |
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| 9. |
- Rojas, Cristian R., et al.
(författare)
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On the Equivalence of Least Costly and Traditional Experiment Design for Control
- 2008
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 44:11, s. 2706-2715
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we establish the equivalence between least costly and traditional experiment design for control. We consider experiment design problems for both open and closed loop systems. In open loop, equivalence is established for three specific cases, relating to different parametrisations of the covariance expression (i.e. finite and high order approximations) and model structure (i.e. dependent and independently parameterised plant and noise models). In the closed loop setting, we consider only finite order covariance expressions. H(infinity) performance specifications for control are used to determine the bounds on the covariance expression for both the open and closed loop cases.
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| 10. |
- Rojas, Cristian R., 1980-, et al.
(författare)
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Robustness in Experiment Design
- 2012
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Ingår i: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 57:4, s. 860-874
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Tidskriftsartikel (refereegranskat)abstract
- This paper focuses on the problem of robust experiment design, i.e., how to design an input signal which gives relatively good estimation performance over a large number of systems and model structures. Specifically, we formulate the robust experiment design problem utilizing fundamental limitations on the variance of estimated parametric models as constraints. Using this formulation we design an input signal for situations where only diffuse a priori information is known about the system. Furthermore, we present a robust version of the unprejudiced optimal input design problem. To achieve this, we first develop a closed form solution for the input spectrum which minimizes the maximum weighted integral of the variance of the frequency response estimate over all model structures.
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