Tesis y Trabajos de Investigación PUCP

URI permanente para esta comunidadhttp://54.81.141.168/handle/123456789/6

El Repositorio Digital de Tesis y Trabajos de Investigación PUCP aporta al Repositorio Institucional con todos sus registros, organizados por grado: Doctorado, Maestría, Licenciatura y Bachillerato. Se actualiza permanentemente con las nuevas tesis y trabajos de investigación sustentados y autorizados, así como también con los que que fueron sustentados años atrás.
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2017 - 20182

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Asesorsearch.filters.applied.operator.equals: search.filters.advisor.Reger, JohannTemasearch.filters.applied.operator.equals: search.filters.subject.Sistemas lineales

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    Optimal control for polynomial systems using the sum of squares approach
    (Pontificia Universidad Católica del Perú, 2018-10-16) Vilcarima Sabroso, Carlos Alberto; Reger, Johann
    The optimal control in linear systems is a widely known problem that leads to the solution of one or two equations of Ricatti. However, in non-linear systems is required to obtain the solution of the Hamilton-Jacobi-Bellman equation (HJB) or variations, which consist of quadratic first order and partial differential equations, that are really difficult to solve. On the other hand, many non-linear dynamical systems can be represented as polynomial functions, where thanks to abstract algebra there are several techniques that facilitate the analysis and work with polynomials. This is where the sum-of-squares approach can be used as a sufficient condition to determine the positivity of a polynomial, a tool that is used in the search for suboptimal solutions of the HJB equation for the synthesis of a controller. The main objective of this thesis is the analysis, improvement and/or extension of an optimal control algorithm for polynomial systems by using the sum of squares approach (SOS). To do this, I will explain the theory and advantages of the sum-of-squares approach and then present a controller, which will serve as the basis for our proposal. Next, improvements will be added in its performance criteria and the scope of the controller will be extended, so that rational systems can be controlled. Finally an alternative will be presented for its implementation, when it is not possible to measure or estimate the state-space variables of the system. Additionally, some examples that validated the results are also presented.
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    Rapid continuous-time identification of linear and nonlinear systems using modulation function approaches
    (Pontificia Universidad Católica del Perú, 2017-03-09) Cieza Aguirre, Oscar Benjamín; Reger, Johann
    At the present, system identification through modulation functions has a wide range of methods. Many of them have reached maturity levels that surpass customary Kalmanfilter approaches for discrete-time identification. In this thesis, the modulation function technique is analyzed in view of its real-time capability, as well as the possible unification of the modulation function methods based on the frequency spectrum, and ability to deal with nonlinearities. Besides, to increase the rate of convergence, the optimal parameter estimation with constraints of Byrski et al. [BFN03] is applied on integrable and convolvable systems. Furthermore, the modulated white Gaussian noise influence on linear systems is examined. The proposed methods together with the Loab-Cahen modulation functions are compared in performance for linear and convolvable systems concerning three different inputs, three normalizations, identification parameters and computational cost.