Tesis de Postgrado Acceso Abierto
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Browsing Tesis de Postgrado Acceso Abierto by Author "AGÜERO VÁSQUEZ, JUAN CARLOS"
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Thesis IDENTIFICACIÓN DE MODELOS DE VIBRACIONES PARA CONTROL DE SISTEMAS DE ÓPTICA ADAPTATIVA(2018) GONZALEZ PEREZ, KAREN FERNANDA; AGÜERO VÁSQUEZ, JUAN CARLOS; Universidad Tecnica Federico Santa Maria UTFSM ELECTRONICA; CARVAJAL GUERRA, RODRIGO JAVIEREn todos los principales observatorios astronomicos terrestres, la optica adaptativa(AO) se ha convertido en una tecnica intrínseca para acercar las observaciones cient íficasal límite de difraccion de los instrumentos astronomicos. Esto se debe a que AO permitela compensacion de las aberraciones ópticas causadas por la turbulencia atmosferica,as como las vibraciones de la estructura del telescopio inducidas por elementos dentrode la instrumentacion del sistema (como ventiladores y bombas de enfriamiento), elviento y los movimientos del telescopio. Ya que las vibraciones afectan fuertemente elrendimiento de los sistemas AO y di cultan el logro de imagenes de buena calidad,es necesario obtener un modelo de estas vibraciones para posteriormente desarrollartecnicas de control simples, pero efectivas, que se puedan implementar en tiempo real.Es por ello que en esta tesis se propone caracterizar estas vibraciones modelandolascomo una combinacion lineal de osciladores alimentados cada uno de ellos por un ruidoe identi cando dichos osciladores de tiempo continuo utilizando un muestreo regular. Serepresenta el modelo del oscilador como un modelo autoregresivo en tiempo continuo paraluego obtener su modelo equivalente en tiempo discreto, en funcion de los parametros delThesis IDENTIFICATION AND CONTROL METHODS UTILIZING RANK AND CARDINALITY OPTIMIZATION APPROACH(2017) URRUTIA BUSTOS, GABRIEL ANDRÉS; AGÜERO VÁSQUEZ, JUAN CARLOS; Universidad Tecnica Federico Santa Maria UTFSM ELECTRONICAThis Thesis addresses a class of optimization problems that can be found in severalareas, such as system identi cation and control. Particularly, these problems are formulatedby using rank and cardinality constraints in order to obtain low rank matrices orinduce sparsity of the solution.Rank-constrained optimization problems are found in control and system identi cation.Low-order controller design problems are well known examples where the formulationutilizes Linear Matrix Inequalities (LMIs) and rank constraints over matrices forbounding the controller's order and closed loop stability degree.Promotion of sparsity in identi cation and control problems can bring many practicaladvantages in the nal solution. In model selection, by formulating the identi cationproblem with a cardinality (`0-norm) constraint over the parameter vector, a simpli edor speci c structure of the model can be obtained. In control applications sparsity canbe induced on the solution of an optimal control problem, thus limiting the number ofactive actuators at each time step.Although low-rank and sparsity are desirable characteristics in the solution of manyproblems of interest, solving these type of problems poses computational diculties.Many approaches that rely on approximations and speci c tailored solutions are availablein the literature in order to overcome the inherent complexity of the problem. However, in this work a novel rank-constraint representation is used which, aims to solve (not anapproximation but) a problem that is equivalent to the original in the sense that theyboth have the same global optimum. The resulting problem can also be solved usingstandard nonlinear programming tools.The work hereby presented is divided in three main parts. First, an overview of stateof-the art techniques for solving cardinality and rank-constrained problems is shown.The second part of the thesis presents optimization problems with cardinality constraintsin the eld of model selection, parameter estimation and optimal control.The third part of the thesis addresses a rank-constrained optimization problem whendesigning a low-order controller with prescribed degree of stability. The formulation ofthis problem includes LMI and rank constraints.
