Search for dissertations about: "Model identification"

Showing result 1 - 5 of 1140 swedish dissertations containing the words Model identification.

  2. 1. On Model Simplification in System Identification

    Author : Bo Wahlberg; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Model simplification; System identification;

    Abstract : This report deals with the connection between system identification and model reduction. We propose an identification algorithm that is based on the least squares identification method and either of the model reduction techniques: Frequency weighted truncated balanced realization or frequency weighted optimal Hankel-norm model reduction. READ MORE

  4. 2. Modeling, Model Validation and Uncertainty Identification for Power System Analysis

    Author : Tetiana Bogodorova; Luigi Vanfretti; Konstantin Turitsyn; Francisco Gonzalez-Longatt; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Power system modelling; model validation; parameter identification; uncertainty identification; Modelica; Electrical Engineering; Elektro- och systemteknik;

    Abstract : It is widely accepted that correct system modeling and identification are among the most important issues power system operators face when managing instability and post-contingency scenarios. The latter is usually performed involving special computational tools that allow the operator to forecast, prevent system failure and take appropriate actions according to protocols for different contingency cases in the system. READ MORE

  5. 3. Stochastic model updating and model selection with application to structural dynamics

    Author : Majid Khorsand Vakilzadeh; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Finite element model; Bayesian model selection; Bayesian model updating; stochastic simulation; Bootstrapping; Subspace system identification; Uncertainty quantification;

    Abstract : Uncertainty induced by our incomplete state of knowledge about engineering systems and their surrounding environment give rise to challenging problems in the process of building predictive models for the system behavior. One such challenge is the model selection problem, which arises due to the existence of invariably multiple candidate models with different mathematical forms to represent the system behavior, and so there is a need to assess their plausibility based on experimental data. READ MORE

  6. 4. Indirect System Identification for Unknown Input Problems : With Applications to Ships

    Author : Jonas Linder; Martin Enqvist; Fredrik Gustafsson; Alexandre Sanfelice Bazanella; Linköpings universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; System identification; Model structure; Unknown inputs; Indirect input measurements; Physical models; Instrumental variable; Closed loop; Graybox model; Identifiability; Ship; Marine vessel; Operational safety; Inertial measurement unit;

    Abstract : System identification is used in engineering sciences to build mathematical models from data. A common issue in system identification problems is that the true inputs to the system are not fully known. In this thesis, existing approaches to unknown input problems are classified and some of their properties are analyzed. READ MORE

  7. 5. Vibrational Response Reconstruction and Model Validation

    Author : Anders Johansson; Chalmers tekniska högskola; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; error metrics; response reconstruction; controllability; rig test; drive signal identification; inverse problems; model validation; state space; model updating;

    Abstract : In this thesis, laboratory response reconstruction andcomputational model validation is investigated. The former concernsapplications of control theory as the objective is to reproduce acertain loading for a known component, while the latter concernsoptimization of a parameterized model as the objective is to modifya computational model to mimic a certain component's behavior. READ MORE