Search for dissertations about: "Lagrange method"
Showing result 1 - 5 of 33 swedish dissertations containing the words Lagrange method.
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1. Adaptive Finite Element Methods for Optimal Control Problems
Abstract : In this thesis we study the numerical solution of optimal control problems. The problems considered consist of a system of differential equations, the state equations, which are governed by a control variable. The goal is to determine the states and controls which minimize a given cost functional. READ MORE
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2. Optimisation and control of boundary layer flows
Abstract : Both optimal disturbances and optimal control are studied by means of numerical simulations for the case of the flat-plate boundary-layer flow. The optimisation method is the Lagrange multiplier technique where the objective function is the kinetic energy of the flow perturbations and the constraints involve the linearised Navier–Stokes equations. READ MORE
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3. Optimisation and control of shear flows
Abstract : Transition to turbulence and flow control are studied by means of numerical simulations for different simple shear flows. Linear and non-linear optimisation methods using the Lagrange multiplier technique are employed. READ MORE
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4. Ghosts and machines : regularized variational methods for interactive simulations of multibodies with dry frictional contacts
Abstract : A time-discrete formulation of the variational principle of mechanics is used to provide a consistent theoretical framework for the construction and analysis of low order integration methods. These are applied to mechanical systems subject to mixed constraints and dry frictional contacts and impacts---machines. READ MORE
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5. Likelihood-Based Panel Unit Root Tests for Factor Models
Abstract : The thesis consists of four papers that address likelihood-based unit root tests for panel data with cross-sectional dependence arising from common factors.In the first three papers, we derive Lagrange multiplier (LM)-type tests for common and idiosyncratic unit roots in the exact factor models based on the likelihood function of the differenced data. READ MORE