| 41. |
- Gerdin, Markus, 1977-, et al.
(författare)
-
Parameter Estimation in Linear Differential-Algebraic Equations
- 2003
-
Ingår i: Proceedings of the 13th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 9780080437095 ; , s. 1530-
-
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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| 42. |
- 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. - Linköping : Linköping University Electronic Press. - 0780395670 ; , s. 350-355
-
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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| 43. |
- Gillberg, Jonas, et al.
(författare)
-
Frequency-Domain Identification of Continuous-Time ARMA Models from Sampled Data
- 2009
-
Ingår i: Automatica. - Linköping : Elsevier. - 0005-1098 .- 1873-2836. ; 45:6, s. 1371-1378
-
Tidskriftsartikel (refereegranskat)abstract
- The subject of this paper is the direct identification of continuous-time autoregressive moving average (CARMA) models. The topic is viewed from the frequency domain perspective which then turns the reconstruction of the continuous-time power spectral density (CT-PSD) into a key issue. The first part of the paper therefore concerns the approximate estimation of the CT-PSD from uniformly sampled data under the assumption that the model has a certain relative degree. The approach has its point of origin in the frequency domain Whittle likelihood estimator. The discrete- or continuous-time spectral densities are estimated from equidistant samples of the output. For low sampling rates the discrete-time spectral density is modeled directly by its continuous-time spectral density using the Poisson summation formula. In the case of rapid sampling the continuous-time spectral density is estimated directly by modifying its discrete-time counterpart.
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| 44. |
- Gillberg, Jonas, et al.
(författare)
-
Frequency Domain Identification of Continuous-Time Output Error Models : Part I: Uniformly Sampled Data and Frequency Function Approximation
- 2010
-
Ingår i: Automatica. - Linköping : Elsevier. - 0005-1098 .- 1873-2836. ; 46:1, s. 1-10
-
Tidskriftsartikel (refereegranskat)abstract
- This paper treats several aspects relevant to identification of continuous-time Output error (OE) models based on sampled data. The exact method for doing this is well known both for data given in the time and frequency domains. This approach becomes somewhat complex, especially for non-uniformly sampled data. We study various ways to approximate the exact method for reasonably fast sampling. While an objective is to gain insights into the non-uniform sampling case, this paper only gives explicit results for uniform sampling.
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| 45. |
- Gillberg, Jonas, et al.
(författare)
-
Frequency Domain Identification of Continuous-Time Output Error Models : Part II: Non-Uniformly Sampled Data and B-Spline Output Approximation
- 2010
-
Ingår i: Automatica. - Linköping : Elsevier. - 0005-1098 .- 1873-2836. ; 46:1, s. 11-18
-
Tidskriftsartikel (refereegranskat)abstract
- This paper treats several aspects relevant to the identification of continuous-time output error (OE) models based on non-uniformly sampled output data. The exact method for doing this is well known in the time domain, where the continuous-time system is discretized, simulated and the result is fitted in a mean square sense to measured data. The material presented here is based on a method proposed in a companion paper (Gillberg andamp; Ljung, 2010) which deals with the same topic but for the case of uniformly sampled data. In this text it will be shown how that method suggests that the output should be reconstructed using a B-spline with uniformly distributed knots. This representation can then be used to directly identify the continuous-time system without proceeding via discretization. Only the relative degree of the model is used to choose the order of the spline.
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| 46. |
- Glad, Torkel, 1947-, et al.
(författare)
-
Controllers for Amplitude Limited Model Error Models
- 2005
-
Ingår i: Proceedings of the 16th IFAC World Congress. - Linköping : Linköping University Electronic Press. - 9783902661753 ; , s. 662-662
-
Konferensbidrag (refereegranskat)abstract
- In this paper, systems where information about model accuracy is contained in a model error model are considered. The validity of such a model is typically restricted to input signals that are limited in amplitude. It is then natural to require the same amplitude restriction when designing controllers. The resulting implications for controller design are investigated in both the continuous and the discrete time case.
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| 47. |
- Glad, Torkel, 1947-, et al.
(författare)
-
Robustness Guarantees for Linear Control Designs with an Estimated Nonlinear Model Error Model
- 2004
-
Ingår i: International Journal of Robust and Nonlinear Control. - Linköping : John Wiley & Sons. - 1049-8923 .- 1099-1239. ; 14:11, s. 959-970
-
Tidskriftsartikel (refereegranskat)abstract
- Much attention in robust identification and control has been focused on linear low order models approximating high order linear systems. We consider the more realistic situation with a linear model approximating a nonlinear system. We describe how a nonlinear model error model can be developed, that allows a complete linear design process that results in a closed loop system with performance robustness guarantees (in terms of gain from disturbance to output) against the nonlinear error. Clearly the design can be successful only if the linear model is a reasonably good approximation of the system. A particular aspect of the design process is to define a workable definition of 'practical stability' for robust control design, with possible non-linear model errors. We use affine norms for that purpose.
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| 48. |
- Gunnarsson, Svante, et al.
(författare)
-
Frequency Domain Description of the Tracking Capability and Disturbance Rejection Trade-off in Recursive Identification
- 1989
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Ingår i: Proceedings of the 1989 International Conference on Acoustics, Speech and Signal Processing. - Linköping : Linköping University. ; , s. 2077-2080
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A study is made of three recursive identification algorithms with respect to their tracking capability and disturbance sensitivity. The algorithms are applied to the identification of time-varying systems with finite impulse response. The performance of the algorithms are measured in terms of the mean square error of the estimated transfer function. Using asymptotic methods, explicit expressions for the mean square error are derived, and these expressions are used to evaluate the performance of the algorithms when applied to systems with different behavior.
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| 49. |
- Guo, Lei, et al.
(författare)
-
Performance Analysis of General Tracking Algorithms
- 1994
-
Ingår i: Proceedings of the 33rd IEEE Conference on Decision and Control. - Linköping : Linköping University. - 0780319680 ; , s. 2851-2855 vol.3
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A general family of tracking algorithms for linear regression models is studied. It includes the familiar LMS (gradient approach), RLS (recursive least squares) and KF (Kalman filter) based estimators. The exact expressions for the quality of the obtained estimates are complicated. Approximate, and easy-to-use, expressions for the covariance matrix of the parameter tracking error are developed. These are applicable over whole time interval, including the transient and the approximation error can be explicitly calculated.
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| 50. |
- Guo, Lei, et al.
(författare)
-
Tracking Performance Analysis of the Forgetting Factor RLS Algorithm
- 1992
-
Ingår i: Proceedings of the 31st IEEE Conference on Decision and Control. - 0780308727 ; , s. 688-693 vol.1
-
Konferensbidrag (refereegranskat)abstract
- The authors present a theoretical analysis for the performance of the standard forgetting factor recursive least squares (RLS) algorithm used in the tracking of time-varying linear regression models. Under some explicit excitation conditions on the regressors, it is shown that the parameter tracking error is on the order O(μ+γ2/μ), where μ=1-λ, λ is the forgetting factor, and γ is the quantity reflecting the speed of parameter variation. Furthermore, for a large class of weakly dependent regressors, simple approximations for the covariance matrix of this error are derived. These approximations are not asymptotic in nature: they hold over all time intervals and for all μ in a certain region.
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