Sökning: "Håkan Hjalmarsson"

Visar resultat 1 - 5 av 26 avhandlingar innehållade orden Håkan Hjalmarsson.

  1. 1. Aspects in Incomplete Modeling in System Identification

    Författare :Håkan Hjalmarsson; Linköpings universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

    Sammanfattning : This thesis considers several aspects of the system identification problem. The major issues, however, are how one should represent and assess mode! errors. These issues have come to be central in system identification in recent years - mainly due to their relevance for robust control. LÄS MER

  2. 2. Aspects on Incomplete Modeling in System Identification

    Författare :Håkan Hjalmarsson; Robert Kosut; Linköping University; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SRA - ICT; SRA - Informations- och kommunikationsteknik;

    Sammanfattning : .... LÄS MER

  3. 3. On Estimation of Model Quality in System Identification

    Författare :Håkan Hjalmarsson; Graham C Goodwin; Linköpings universitet; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; SRA - ICT; SRA - Informations- och kommunikationsteknik; Automatic control; Reglerteknik;

    Sammanfattning : .... LÄS MER

  4. 4. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions

    Författare :Mohamed Abdalmoaty; Håkan Hjalmarsson; Adrian Wills; KTH; []
    Nyckelord :Prediction Error Method; Maximum Likelihood; Data-driven; Learning; Stochastic; Nonlinear; Dynamical Models; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Estimation; Process Disturbance; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. LÄS MER

  5. 5. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors

    Författare :Mohamed Abdalmoaty; Håkan Hjalmarsson; Jimmy Olsson; KTH; []
    Nyckelord :ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; TEKNIK OCH TEKNOLOGIER; NATURAL SCIENCES; ENGINEERING AND TECHNOLOGY; Stochastic Nonlinear Systems; Nonlinear System Identification; Learning Dynamical Models; Maximum Likelihood; Estimation; Process Disturbance; Prediction Error Method; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning : The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. LÄS MER