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  • 1.
    Albertos, Pedro
    et al.
    Polytechnical University of Valencia, Spain.
    Goodwin, Graham C.
    University of Newcastle, Australia.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Pseudo Linear Regression Algorithm for On-Line Parameter Estimation with Missing Data1992Rapport (Övrigt vetenskapligt)
  • 2.
    Andersson, Torbjörn
    et al.
    Linköpings universitet, Institutionen för medicin och hälsa, Medicinsk radiologi. Linköpings universitet, Hälsouniversitetet.
    Pucar, Predrag
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Projekt operatörsverktyg, delprojekt 4: Modeller för massatransport och beräkning av uppehållstid i fiberlinjen. Slutrapport1992Rapport (Övrigt vetenskapligt)
    Ladda ner fulltext (ps)
    FULLTEXT01
  • 3.
    Gustafsson, Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf J.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Best Choice of Coordinate System for Tracking Coordinated Turns1995Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A standard approach to tracking is to use the extended Kalman filter (EKF) applied to a nonlinear state-space model. We compare two conceivable choices of state variables for modeling civil aircrafts. One where Cartesian velocities are used and one where absolute velocity and heading angle are used. In both choices, Cartesian coordinates are used for position and angular velocity for turning. It is shown that the latter state vector always performs better. This is proven by considering the linearization error made in the extended Kalman filter applied either to a time-continuous model or a discretized model. The result is supported by a Monte Carlo simulation study.

  • 4.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Recursive EM Algorithm for Identification of ARX-Models Subject to Missing Data1992Rapport (Övrigt vetenskapligt)
  • 5.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    An Extension of the Simulation and Analysis Program ANLAB1983Rapport (Övrigt vetenskapligt)
  • 6.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    An On-Line Threshold Selector for Failure Detection1992Rapport (Övrigt vetenskapligt)
  • 7.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Analysis of Identified 2-D Noncausal Models1991Rapport (Övrigt vetenskapligt)
    Abstract [en]

    There are two approaches to the identification of noncausal autoregressive systems in two dimensions differing in the assumed noise model. For both approaches, the maximum likelihood estimator formulated in the frequency domain is presented. The Fisher information matrix is evaluated and found to be the sum of a block-Toeplitz and a block-Hankel matrix. The variance of the parameters, however, cannot be used for comparison of the two approaches, so the variance in the frequency domain is evaluated, assuming that the true system in each case can be described by a model of that type, possibly high-order. In particular, the variance of the spectrum estimate is derived. If the number of parameters tends to infinity, it is shown that the two approaches give the same spectrum estimate variance. The question of which set of true spectra can be described by the respective approaches is discussed.

  • 8.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Analysis of Identified 2-D Noncausal Models1991Rapport (Övrigt vetenskapligt)
    Abstract [en]

    There are two approaches to the identification of noncausal autoregressive systems in two dimensions differing in the assumed noise model. For both approaches, the maximum likelihood estimator formulated in the frequency domain is presented. The Fisher information matrix is evaluated and found to be the sum of a block-Toeplitz and a block-Hankel matrix. The variance of the parameters, however, cannot be used for comparison of the two approaches, so the variance in the frequency domain is evaluated, assuming that the true system in each case can be described by a model of that type, possibly high-order. In particular, the variance of the spectrum estimate is derived. If the number of parameters tends to infinity, it is shown that the two approaches give the same spectrum estimate variance. The question of which set of true spectra can be described by the respective approaches is discussed.

  • 9.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    ANLAB: The Manual1985Rapport (Övrigt vetenskapligt)
  • 10.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Digital Protective Relaying through Recursive Least Squares Identification1987Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Parameter estimation is applied to the problem of transmission line protection. The Fourier coefficients of voltage and current are estimated using recursive least-squares identification. The estimates are then used to detect short circuits. The method is evaluated using data generated by the program EMTP

  • 11.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Estimate of Average Residence Time given an Identified ARX-Model1992Rapport (Övrigt vetenskapligt)
  • 12.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Estimation of Average Residence Time Given an Identified AR-Model1992Rapport (Övrigt vetenskapligt)
  • 13.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Frequency Domain Accuracy of Identified 2-D Causal Models1989Ingår i: Proceedings of the 1989 International Conference on Acoustics, Speech and Signal Processing, 1989, s. 2294-2297Konferensbidrag (Refereegranskat)
    Abstract [en]

    A study is made of parametric estimation of 2-D transfer functions using the least-squares method which is the dominant method for causal systems. The analysis concentrates on the frequency-domain accuracy of the estimated models. There exist results for the accuracy of the parameter estimates. The parameters are asymptotically Gaussian distributed. The variance of the polynomial in the frequency domain can be expressed using these results for the parameters. This, however, gives no insight into the dependence on the true transfer function. An illuminating result is obtained if the model order tends to infinity. The limiting results show good correspondence with Monte-Carlo simulations for small data sets obtained with low model orders.

  • 14.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Frequency Domain Accuracy of Identified 2-D Causal Models1990Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A study is made of parametric estimation of 2-D transfer functions using the least-squares method which is the dominant method for causal systems. The analysis concentrates on the frequency-domain accuracy of the estimated models. There exist results for the accuracy of the parameter estimates. The parameters are asymptotically Gaussian distributed. The variance of the polynomial in the frequency domain can be expressed using these results for the parameters. This, however, gives no insight into the dependence on the true transfer function. An illuminating result is obtained if the model order tends to infinity. The limiting results show good correspondence with Monte-Carlo simulations for small data sets obtained with low model orders.

  • 15.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Identification of Time Varying Systems and Application of System Identification to Signal Processing1986Licentiatavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    Part I

    A new approach to identification of time varying systems is presented, and evaluated using computer simulations. The new approach is built upon the similarities between recursive least squares identification and Kalman filtering.

    The parameter variations are modelled as process noise in a state space model and then identified using adaptive Kalman filtering. A method for adaptive Kalman filtering is derived and analysed. The simulations indicate that this new approach is superior to previous methods based on adjusting the forgetting factor. This improvement is however gained at the price of a signification increase in computational complexity.

    Part II

    In this part we apply parameter estimation to the problem of transmission line protection.

    One approach based on recursive least squares identification is presented. The method has ben tested using simulated data generated by the program EMTP.

    Another approach based on the theory of travelling waves is also discussed.

    Part III

    In this part a method for input estimation or deconvolution is presented. The basis of the method is to use a parametrized model the input signal. To use the method we should thus be able to express the input signal as a function of some unknown parameters and time. The algorithms simultaneously estimates the parameters of the input signal and the parameters of the system transfer function. The presentation here is restricted to transfer functions of all pole type, i.e. ARX-models. The method can be extended to handle zeros in the transfer function. The computational burden would however increase significantly. The algorithm uses efficient numerical methods, as for instance QR-factorization thorugh Householder transformation.

    The algorithm is in this paper applied to a problem in speech coding. It has been observed that the quality of synthesized speech can be improved, if a more detailed model than an impulse train is used for the pitch pulses, see Fant (1980). It is here shown how the method presented in this paper can be used to estimate the system parameters of the speech production and the parameters of the glottal pulse simultaneously.

  • 16.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Identification of Time Varying Systems Through Adaptive Kalman Filtering1987Ingår i: Proceedings of the 10th IFAC World Congress, 1987Konferensbidrag (Refereegranskat)
  • 17.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Identification of Time Varying Systems through Adaptive Kalman Filtering1987Rapport (Övrigt vetenskapligt)
  • 18.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Missing Data M-Files: User's Guide1992Rapport (Övrigt vetenskapligt)
  • 19.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On System Identification in one and two Dimensions with Signal Processing Applications1988Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    This thesis consists of four parts, with system identification as the common theme. The first part studies the asymptotic properties of two-dimensional identification methods. In the second part an approach to identification of time varying systems is presented. Part three applies system identification to the problem of transmission line protection. Finally part four deals with input estimation in speech coding.

    Part I is devoted to system identification in two dimensions. First we study the asymptotic properties of the estimates as the number of data tends to infinity. The main objective is to investigate what happens if the model order also tends to infinity. The focus is on frequency expressions of the extimation variance. The analysis covers both the least squares method for causal models, and the maximum likelihood method for noncausal models.

    In Part II we study one approach to identification of time varying sytems. The parameter variations are modelled as process noise in a state space model, and identified using adaptive Kalman filtering. A method for adaptive Kalman filtering is derived and analysed. The simulations indicate that this new approach is superior to previous methods based on adjusting the forgetting factor. The improvement is however gained at the price of a significant increase in computational complexity.

    Part III describes the use of recursive identification in protective relaying. The Fourier coefficients of voltage and current are estimated using recursive least squares identification. The estimates are then used to detect short circuits. The method is evaluated using data generated by the standard program EMTP.

    In Part IV a method for inverse glottal filtering is presented. The basis of the method is to use a parameterized model of the input signal, i.e. the glottal pulses. The algorithm simultaneously estimates the parameters of the input signal and the parameters of the system transfer function, the vocal tract model. The presentation is restricted to transfer functions of all-pole type.

  • 20.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On the Use of Linear Interpolation in Identification Subject to Missing Data1992Rapport (Övrigt vetenskapligt)
  • 21.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    System Identification Subject to Missing Data1990Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper we study parameter estimation when the measurement information may be incomplete. As a basic system representation we use an ARX-model. The presentation covers both missing output and input. First reconstruction of the missing values is discussed. The reconstruction is based on a state-space formulation of the system, and is performed using the Kalman filtering or fixed-interval smoothing formulas. Several approaches to the identification problem are then presented, including a new method based on the so called EM algorithm. The different approaches are tested and compared using Monte-Carlo simulations. The choice of method is always a trade off between estimation accuracy and computational complexity. According to the simulations the gain in accuracy using the EM method can be considerable if much data are missing.

  • 22.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    System Identification Subject to Missing Data1991Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper we study parameter estimation when the measurement information may be incomplete. As a basic system representation we use an ARX-model. The presentation covers both missing output and input. First reconstruction of the missing values is discussed. The reconstruction is based on a state-space formulation of the system, and is performed using the Kalman filtering or fixed-interval smoothing formulas. Several approaches to the identification problem are then presented, including a new method based on the so called EM algorithm. The different approaches are tested and compared using Monte-Carlo simulations. The choice of method is always a trade off between estimation accuracy and computational complexity. According to the simulations the gain in accuracy using the EM method can be considerable if much data are missing.

  • 23.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Graebe, Stefan F.
    University of Newcastle, Australia.
    Model Reduction for PID Control1992Rapport (Övrigt vetenskapligt)
  • 24.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Granberg, Bertil
    Identifications on Data from the Skoghall Pulp Mill (In Swedish)1991Rapport (Övrigt vetenskapligt)
  • 25.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Bayesian Approach to Manoeuvre Tracking and Detection1992Rapport (Övrigt vetenskapligt)
  • 26.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Multiple Model Approach to Manouvre Tracking and Detection1992Rapport (Övrigt vetenskapligt)
  • 27.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hill, David J.
    University of Newcastle, Australia.
    Power Plant Monitoring: Survey and Directions for Future Research1992Rapport (Övrigt vetenskapligt)
  • 28.
    Isaksson, Alf J.
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för ekonomisk och industriell utveckling, Produktionsekonomi. ABB AB, Corporate Research, SE-721 78 Västerås, Sweden.
    Some aspects of industrial system identification2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    The most important and time consuming part of an industrial application of control is the modelling. It may take 50 per cent or more of the entire project. Therefore a major challenge for a control systems supplier like ABB is to constantly try to decrease the engineering effort for modelling.

    This paper discusses some different aspects of modelling and identification originating from application in many different industries such as pulp and paper, rolling mills, power plants and specialty chemicals.

    Ladda ner fulltext (pdf)
    Some aspects of industrial system identification
  • 29.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Strömberg, Jan-Erik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On Recursive Construction of Trees as Models of Dynamical Systems1991Rapport (Övrigt vetenskapligt)
    Abstract [en]

    An issue that is of importance for control applications is discussed: how to construct the trees online, i.e. recursively, as more and more data become available. A theorem regarding recursive tree-building is stated and proved, and implementation issues are considered.

  • 30.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Input Estimation with Application to Speech Coding1984Rapport (Övrigt vetenskapligt)
  • 31.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Input Estimation with Application to Speech Coding1987Rapport (Övrigt vetenskapligt)
    Abstract [fr]

    Dans ce papier une méthode pour l'estimation de l'entrée (ou déconvolution) est présentée. La méthode est basée principalement sur l'utilisation d'une certaine paramétrization du modèle du signal d'entrée. Pour utiliser cette méthode, nous devons être capable d'exprimer le signal d'entrée en fonction de quelques paramètres inconnues et du temps. L'algorithme est conçu pour estimer, simultanément, les paramètres du signal d'entrée et ceux de la fonction de transfert du système. On se limite à l'étude des systèmes dont la fonction de transfert ne comportant que des pôles (c.à.d modèles ARX). La méthode peut être étendue pour consider aussi les zéros de la fonction de transfert. Il est évident que ceci entraîne une augmentation de la charge numérique. L'algorithme est basé sur des méthodes numériques efficaces comme par exemple la factorisation QR utilisant les transformations de Householder. L'application d'un tel algorithme au codage de la parole est présentée. It est à noter que la qualité du signal synthétisé de la parole, peut être nettement améliorée si un modèle plus détaillé est utilisé pour décrire, le modèle du mouvement des cordes vocal plutôt qu'un train d'impulsion. On montre aussi que la méthode envisagée peut être utilisée pour estimer les paramètres du système vocales et ceux du modèle du mouvement des cordes vocales simultanément.

  • 32.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Inverse Glottal Filtering using a Parameterized Input Model1989Ingår i: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 18, nr 4, s. 435-445Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper computational algorithms for inverse glottal filtering are studied. The objective of inverse glottal filtering is to estimate the driving source. A good model for the glottal pulse is useful for, e.g., speech synthesis, speech recognition and speaker diagnostics. One common approach is to use a parameterized model of the input signal, i.e., the glottal pulses. The algorithm presented enables simultaneous estimation of the parameters of the input signal and the parameters of the system transfer function, the vocal tract model. The presentation here is restricted to transfer functions of all-pole type, i.e., AR-models. The method can be extended to handle zeros in the transfer function. The computational burden would, however, increase significantly. The algorithm uses efficient numerical methods, as, for instance, QR-factorization through Householder transformations.

  • 33.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Millnert, Mille
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Inverse Glottal Filtering using a Parameterized Input Model1987Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper computational algorithms for inverse glottal filtering are studied. The objective of inverse glottal filtering is to estimate the driving source. A good model for the glottal pulse is useful for, e.g., speech synthesis, speech recognition and speaker diagnostics. One common approach is to use a parameterized model of the input signal, i.e., the glottal pulses. The algorithm presented enables simultaneous estimation of the parameters of the input signal and the parameters of the system transfer function, the vocal tract model. The presentation here is restricted to transfer functions of all-pole type, i.e., AR-models. The method can be extended to handle zeros in the transfer function. The computational burden would, however, increase significantly. The algorithm uses efficient numerical methods, as, for instance, QR-factorization through Householder transformations.

  • 34.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Corp Research, Sweden.
    Sjöberg, Johan
    Linköpings universitet, Institutionen för systemteknik. Volvo Construct Equipment, Sweden.
    Tornqvist, David
    SenionLab AB, S-58330 Linkoping, Sweden.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Kok, Manon
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Using horizon estimation and nonlinear optimization for grey-box identification2015Ingår i: Journal of Process Control, ISSN 0959-1524, E-ISSN 1873-2771, Vol. 30, s. 69-79Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An established method for grey-box identification is to use maximum-likelihood estimation for the nonlinear case implemented via extended Kalman filtering. In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that, in the linear case, horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman filter is included. For the nonlinear case two special cases are presented where the bias correction can be determined without approximation. A procedure how to approximate the bias correction for general nonlinear systems is also outlined. (C) 2015 Elsevier Ltd. All rights reserved.

  • 35.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan. ABB AB, Sweden.
    Törnqvist, David
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Sjöberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Grey-Box Identification Based on Horizon Estimation and Nonlinear Optimization2009Ingår i: Proceedings of the 41st ISCIE International Symposium on Stochastic Systems, Institute of Systems, Control and Information Engineers , 2009, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman filter is included. A procedure how to approximate the bias correction for nonlinear systems is outlined.

  • 36.
    Isaksson, Alf
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Törnqvist, David
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Sjöberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Grey-Box Identification Based on Horizon Estimation and Nonlinear Optimization2010Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman filter is included. A procedure how to approximate the bias correction for nonlinear systems is outlined.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 37.
    Ljung, Lennart
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Wallin, Ragnar
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    An Iterative Method for Identification of ARX Models from Incomplete Data2000Ingår i: Proceedings of the 39th IEEE Conference on Decision and Control, IEEE , 2000, s. 203-208 vol.1Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper describes a very simple and intuitive algorithm to estimate parameters of ARX models from incomplete data sets. An iterative scheme involving two least squares steps and a bias correction is all that is needed.

  • 38.
    Millnert, Mille
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Input Estimation with Application Speech Coding1985Ingår i: Proceedings of the 1985 GRETSI Conference, 1985Konferensbidrag (Refereegranskat)
  • 39.
    Millnert, Mille
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ottersten, Björn
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Skeppstedt, Anders
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Viberg, Mats
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Methods for Signal Modelling1988Ingår i: Proceedings of the 1988 Workshop on Digital Transmission, 1988Konferensbidrag (Övrigt vetenskapligt)
  • 40.
    Peretzki, Daniel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Carvalho Bittencourt, André
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Data Mining of Historic Data for Process Identification2011Ingår i: Proceedings of the 2011 AIChE Annual Meeting, American Institute of Chemical Engineers, 2011, s. 1027-1033Konferensbidrag (Refereegranskat)
    Abstract [en]

    Performing experiments for system identication is often a time-consuming task which may also interfere with the process operation. With memory prices going down, it is more and more common that years of process data are stored (without compression) in a history database. The rationale for this work is that in such stored data there must already be intervals informative enough for system identication. Therefore, the goal of this project was to find an algorithm that searches and marks intervals suitable for process identication (rather than performing completely automatic system identication). For each loop, 4 stored variables are required; setpoint, manipulated variable, process output and mode of the controller.

    The proposed method requires a minimum of knowledge of the process and is implemented in a simple and ecient recursive algorithm. The essential features of the method are the search for excitation of the input and output, followed by the estimation of a Laguerre model combined with a chi-square test to check that at least one estimated parameter is statistically signicant. The use of Laguerre models is crucial to handle processes with deadtime without explicit delay estimation. The method was tested on three years of data from more than 200 control loops. It was able to find all intervals in which known identication experiments were performed as well as many other useful intervals in closed/open loop operation.

  • 41.
    Peretzki, Daniel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Carvalho Bittencourt, André
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Data Mining of Historic Data for Process Identification2011Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Performing experiments for system identication is often a time-consuming task which may also interfere with the process operation. With memory prices going down, it is more and more common that years of process data are stored (without compression) in a history database. The rationale for this work is that in such stored data there must already be intervals informative enough for system identication. Therefore, the goal of this project was to find an algorithm that searches and marks intervals suitable for process identication (rather than performing completely automatic system identication). For each loop, 4 stored variables are required; setpoint, manipulated variable, process output and mode of the controller.

    The proposed method requires a minimum of knowledge of the process and is implemented in a simple and ecient recursive algorithm. The essential features of the method are the search for excitation of the input and output, followed by the estimation of a Laguerre model combined with a chi-square test to check that at least one estimated parameter is statistically signicant. The use of Laguerre models is crucial to handle processes with deadtime without explicit delay estimation. The method was tested on three years of data from more than 200 control loops. It was able to find all intervals in which known identication experiments were performed as well as many other useful intervals in closed/open loop operation.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 42.
    Rosander, Peter
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Löfberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Performance Analysis of Robust Averaging Level Control2011Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Frequent inlet flow changes, especially in the same direction, typically cause problems for averaging level controllers. To obtain optimal flow filtering while being robust towards future inlet flow upsets closed loop robust MPC was used. Its performance and robustness is analyzed and compared to the optimal averaging level controller. The knowledge gained from the robust MPC exercise is also used to propose a robustification of the optimal controller. Both the analysis and the simulation results show that the robust controller obtains comparable flow filtering as the optimal controller even when inlet flow changes are sparse while handling frequent upsets considerably better.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 43.
    Rosander, Peter
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Löfberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Performance Analysis of Robust Averaging Level Control2012Ingår i: Proceedings of the 2012 Conference on Chemical Process Control, 2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    Frequent inlet flow changes, especially in the same direction, typically cause problems for averaging level controllers. To obtain optimal flow filtering while being robust towards future inlet flow upsets closed loop robust MPC was used. Its performance and robustness is analyzed and compared to the optimal averaging level controller. The knowledge gained from the robust MPC exercise is also used to propose a robustification of the optimal controller. Both the analysis and the simulation results show that the robust controller obtains comparable flow filtering as the optimal controller even when inlet flow changes are sparse while handling frequent upsets considerably better

  • 44.
    Rosander, Peter
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Löfberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Practical Control of Surge Tanks Suffering from Frequent Inlet Flow Upsets2011Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In the presence of frequent inlet flow upsets, tuning of averaging level controllers is typically quite complicated since not only the size of the individual steps but also the time in between the subsequent steps need to considered. One structured way to achieve optimal filtering for such a case is to use Robust Model Predictive Control. The robust MPC controller is, however, quite computationally demanding and not easy to implement. In this paper two linear controllers, which mimic the behavior of the robust MPC, are proposed. Tuning guidelines to avoid violation of the tank level constraints as well as to achieve optimal filtering are presented.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 45.
    Rosander, Peter
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Löfberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Practical Control of Surge Tanks Suffering from Frequent Inlet Flow Upsets2012Ingår i: Proceedings of the 2nd IFAC Conference on Advances in PID Control, 2012, s. 258-263Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the presence of frequent inlet flow upsets, tuning of averaging level controllers is typically quite complicated since not only the size of the individual steps but also the time in between the subsequent steps need to considered. One structured way to achieve optimal filtering for such a case is to use Robust Model Predictive Control. The robust MPC controller is, however, quite computationally demanding and not easy to implement. In this paper two linear controllers, which mimic the behavior of the robust MPC, are proposed. Tuning guidelines to avoid violation of the tank level constraints as well as to achieve optimal filtering are presented.

  • 46.
    Rosander, Peter
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Löfberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Robust Averaging Level Control2011Ingår i: Proceedings of the 2011 AIChE Annual Meeting, 2011Konferensbidrag (Refereegranskat)
    Abstract [en]

    Frequent inlet flow changes typically cause problems for averaging level controllers. For a frequently changing inlet flow the upsets do not occur when the system is in steady state and the tank level at its set-point. For this reason the tuning of the level controller gets quite complicated, since not only the size of the upsets but also the time in between them relative to the hold up of the tank have to be considered. One way to obtain optimal flow filtering while directly accounting for future inlet flow upsets is to use closed-loop robust MPC, as proposed here. The behavior of the robust MPC controller differs from earlier proposed level controllers as it does not return the tank level to a fixed set-point following an inlet flow upset. Guidelines on the tuning of the controller is presented and its performance is compared to that of a previously proposed MPC approach.

  • 47.
    Rosander, Peter
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Löfberg, Johan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Forsman, Krister
    Perstorp AB, Sweden.
    Robust Averaging Level Control2011Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Frequent inlet flow changes typically cause problems for averaging level controllers. For a frequently changing inlet flow the upsets do not occur when the system is in steady state and the tank level at its set-point. For this reason the tuning of the level controller gets quite complicated, since not only the size of the upsets but also the time in between them relative to the hold up of the tank have to be considered. One way to obtain optimal flow filtering while directly accounting for future inlet flow upsets is to use closed-loop robust MPC, as proposed here. The behavior of the robust MPC controller differs from earlier proposed level controllers as it does not return the tank level to a fixed set-point following an inlet flow upset. Guidelines on the tuning of the controller is presented and its performance is compared to that of a previously proposed MPC approach.

    Ladda ner fulltext (pdf)
    FULLTEXT01
    Ladda ner fulltext (pdf)
    FULLTEXT03
  • 48.
    Strömberg, Jan-Erik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Towards Online Tree Construction1992Rapport (Övrigt vetenskapligt)
  • 49.
    Strömberg, Jan-Erik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Zrida, Jalel
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Neural Trees: Using Neural Nets in a Tree Classifier Structure1991Ingår i: Proceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing, IEEE , 1991, Vol. 1, s. 137-140Konferensbidrag (Refereegranskat)
    Abstract [en]

    The concept of tree classifiers is combined with the popular neural net structure. Instead of having one large neural net to capture all the regions in the feature space, the authors suggest the compromise of using small single-output nets at each tree node. This hybrid classifier is referred to as a neural tree. The performance of this classifier is evaluated on real data from a problem in speech recognition. When verified on this particular problem, it turns out that the classifier concept drastically reduces the computational complexity compared with conventional multilevel neural nets. It is also noted that these data make it possible to grow trees online from a continuous data stream.

  • 50.
    Strömberg, Jan-Erik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Zrida, Jalel
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Neural Trees: Using Neural Nets in a Tree Classifier Structure1991Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The concept of tree classifiers is combined with the popular neural net structure. Instead of having one large neural net to capture all the regions in the feature space, the authors suggest the compromise of using small single-output nets at each tree node. This hybrid classifier is referred to as a neural tree. The performance of this classifier is evaluated on real data from a problem in speech recognition. When verified on this particular problem, it turns out that the classifier concept drastically reduces the computational complexity compared with conventional multilevel neural nets. It is also noted that these data make it possible to grow trees online from a continuous data stream.

12 1 - 50 av 53
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