Search for dissertations about: "Gray-Box Identification."
Showing result 1 - 5 of 13 swedish dissertations containing the words Gray-Box Identification..
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1. Multivariable Frequency-Domain Identification of Industrial Robots
Abstract : Industrirobotar är idag en väsentlig del i tillverkningsindustrin där de bland annat används för att minska kostnader, öka produktivitet och kvalitet och ersätta människor i farliga eller slitsamma uppgifter. Höga krav på noggrannhet och snabbhet hos robotens rörelser innebär också höga krav på de matematiska modeller som ligger till grund för robotens styrsystem. READ MORE
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2. Regression on Manifolds with Implications for System Identification
Abstract : The trend today is to use many inexpensive sensors instead of a few expensive ones, since the same accuracy can generally be obtained by fusing several dependent measurements. It also follows that the robustness against failing sensors is improved. As a result, the need for high-dimensional regression techniques is increasing. READ MORE
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3. Structural Reformulations in System Identification
Abstract : In system identification, the choice of model structure is important and it is sometimes desirable to use a flexible model structure that is able to approximate a wide range of systems. One such model structure is the Wiener class of systems, that is, systems where the input enters a linear time-invariant subsystem followed by a time-invariant nonlinearity. READ MORE
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4. Identification and Estimation for Models Described by Differential-Algebraic Equations
Abstract : Differential-algebraic equations (DAEs) form the natural way in which models of physical systems are delivered from an object-oriented modeling tool like Modelica. Differential-algebraic equations are also known as descriptor systems, singular systems, and implicit systems. READ MORE
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5. Initialization Methods for System Identification
Abstract : In the system identification community a popular framework for the problem of estimating a parametrized model structure given a sequence of input and output pairs is given by the prediction-error method. This method tries to find the parameters which maximize the prediction capability of the corresponding model via the minimization of some chosen cost function that depends on the prediction error. READ MORE