| 1. |
- Gerdin, Markus, et al.
(författare)
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Global Identifiability of Complex Models, Constructed from Simple Submodels
- 2007
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Rapport (övrigt vetenskapligt)abstract
- It is a typical situation in modern modeling that a total model isbuilt up from simpler submodels, or modules, for example residingin a model library. The total model could be quite complex, whilethe modules are well understood and analysed. A procedure to decide global parameter identifiability for such a collection of modelequations of differential-algebraic nature is suggested. It is shownhow to make use of the natural modularization of the model structure.Basically, global identifiability is obtained if and only if each moduleis identifiable, and the connecting signals can be retrieved fromthe external signals, without knowledge of the values of the parameters.
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| 2. |
- Gerdin, Markus, 1977-, et al.
(författare)
-
On Parameter and State Estimation for Linear Differential-Algebraic Equations
- 2007
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Ingår i: Automatica. - 0005-1098. ; 43, s. 416-425
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Tidskriftsartikel (refereegranskat)abstract
- The current demand for more complex models has initiated a shift away from state-space models towards models described by differential-algebraic equations (DAEs). These models arise as the natural product of object-oriented modeling languages, such as Modelica. However, the mathematics of DAEs is somewhat more involved than the standard state-space theory. The aim of this work is to present a well-posed description of a linear stochastic differential-algebraic equation and more importantly explain how well-posed estimation problems can be formed. We will consider both the system identification problem and the state estimation problem. Besides providing the necessary theory we will also explain how the procedures can be implementedby means of efficient numerical methods.
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| 3. |
- Gerdin, Markus, et al.
(författare)
-
On Parameter and State Estimation for Linear Differential-Algebraic Equations
- 2007
-
Rapport (övrigt vetenskapligt)abstract
- The current demand for more complex models has initiated ashift away from state-space models towards models described bydifferential-algebraic equations (DAEs). These models arise as thenatural product of object-oriented modeling languages, such asModelica. However, the mathematics of DAEs is somewhat more involvedthan the standard state-space theory. The aim of this work is topresent a well-posed description of a linear stochasticdifferential-algebraic equation and more importantly explain howwell-posed estimation problems can be formed. We will consider boththe system identification problem and the state estimationproblem. Besides providing the necessary theory we will also explainhow the procedures can be implemented by means of efficient numericalmethods.
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| 4. |
- Gerdin, Markus, 1977-, et al.
(författare)
-
Parameter Estimation in Linear Differential-Algebraic Equations
- 2003
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Ingår i: Proceedings of the 13th IFAC Symposium on System Identification. - 978-0080437095 ; s. 1530
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Konferensbidrag (refereegranskat)abstract
- This report describes how parameter estimation can be performed in linear DAE systems. Both time domain and frequency domain identification are examined. The results are exemplified on a small system. A potential application for the algorithms is to make parameter estimation in models generated by a modeling language like Modelica.
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| 5. |
- Gerdin, Markus, et al.
(författare)
-
Parameter estimation in linear differential-algebraic equations
- 2003
-
Rapport (övrigt vetenskapligt)abstract
- This report describes how parameter estimation can be performed in linear DAE systems. Both time domain and frequency domain identification are examined. The results areexemplified on a small system. A potential application for thealgorithms is to make parameter estimation in models generatedby a modeling language like Modelica.
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| 6. |
- Gerdin, Markus, 1977-, et al.
(författare)
-
Well-Posedness of Filtering Problems for Stochastic Linear DAE Models
- 2005
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Ingår i: Proceedings of the 44th IEEE Conference on Decision and Control and European Control Conference. - 0-7803-9567-0 ; s. 350-355
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Konferensbidrag (refereegranskat)abstract
- Modern modeling tools often give descriptor or DAE models, i.e., models consisting of a mixture of differential and algebraic relationships. The introduction of stochastic signals into such models in connection with filtering problems raises several questions of well-posedness. The main problem is that the system equations may contain hidden relationships affecting variables defined as white noise. The result might be that certain physical variables get infinite variance or contain formal differentiations of white noise. The paper gives conditions for well-posedness in terms of certain subspaces defined by the system matrices.
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| 7. |
- Gerdin, Markus, et al.
(författare)
-
Well-posedness of Filtering Problems for Stochastic Linear DAE Models
- 2005
-
Rapport (övrigt vetenskapligt)abstract
- Modern modeling tools often give descriptor or DAE models, i.e., modelsconsisting of a mixture of differential and algebraic relationships.The introduction of stochastic signals into such models in connectionwith filtering problems raises several questions of well-posedness. Themain problem is that the system equations may contain hiddenrelationships affectingvariables defined as white noise. The resultmight be that certain physical variables get infinite variance orcontain formal differentiations of white noise.The paper gives conditions for well-posedness in terms of certainsubspaces defined by the system matrices.
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