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dc.contributor.advisorPerez Zuñiga, Carlos Gustavo
dc.contributor.authorVelasquez Elguera, Mario Sebastian
dc.date.accessioned2023-05-11T19:35:04Z
dc.date.available2023-05-11T19:35:04Z
dc.date.created2023
dc.date.issued2023-05-11
dc.identifier.urihttp://hdl.handle.net/20.500.12404/24964
dc.description.abstractNanopositioning and nanomeasuring machines are playing an increasingly important role in the evolution of modern technologies in various fields. The Institute of Process Measure ment and Sensor Technology at Ilmenau University of Technology has been researching for more tan one decade high precisión machines. In this direction, the general objective of this master tesis is the development of aderivative-free model reference adaptive control (DFMRAC) algorithm for the vertical axisofa nanopositioning and nanomeasuring machine. Firstly, a nonlinear unknown friction term is included in the adaptation process of a standard model reference adaptive control (MRAC) and the DFMRAC. Then, the MRAC and DFMRAC algorithms are developed theoretically, in which the DFMRAC stability análisis requiresa Lyapunov-Krasovskii functional to prove that the error signal and the weightpa- rameters are uniformly ultimately bounded (UUB). Thanks to this characteristic, the DFMRAC algorithm does not have the problema of the weight drifting parameters, as MRAC does. Overall, the new adaptive controllers have significantly better results and fine-tuning in the machine. Regarding the sine reference experimental tests with afixed amplitude of 1mm and a frequency from 0.25 Hz to 2 Hz, a reduction of the máximum error and root mean square error (RMSE) of about 95% is achieved in comparison to a simple PI state-feed back controller and the previously applied MRAC with an adaptation weight matrix of lower order. Referring to the step reference tests, with a step height of 10mm and different transition times (which are related to the máximum reached velocity from 1mm/s to 5mm/s) the máximum error and the RMSE are reduced approximately by 60% and 75%, respectively. Furthermore, the corresponding extensions to the unknown input matrix case are developed for the adaptive proposals, however it does not significantly improve the experimental results. The new controllers out performed the previous ones with DFMRAC being the best one because it does not have the drifting weight parameters problem and it is easier to implement (no need to implement any projection method). Finally, eventhough, the new adaptive algorithms have extended the size of the weight matrix and added nonlinearities to the computer calculations, the execution time is only increased by around 1 μs.es_ES
dc.language.isoenges_ES
dc.publisherPontificia Universidad Católica del Perúes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-sa/2.5/pe/*
dc.subjectAlgoritmos--Control adaptativoes_ES
dc.subjectControladores programables--Diseño y construcciónes_ES
dc.subjectNanotecnologíaes_ES
dc.titleApplication of derivative-free adaptive control to a nanopositioning machinees_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
thesis.degree.nameMaestro en Ingeniería de Control y Automatizaciónes_ES
thesis.degree.levelMaestríaes_ES
thesis.degree.grantorPontificia Universidad Católica del Perú. Escuela de Posgrado.es_ES
thesis.degree.disciplineIngeniería de Control y Automatizaciónes_ES
renati.advisor.dni41864666
renati.advisor.orcidhttps://orcid.org/0000-0001-5946-1395es_ES
renati.author.dni73870085
renati.discipline712037es_ES
renati.jurorSotomayor Moriano, Juan Javieres_ES
renati.jurorPerez Zuñiga, Carlos Gustavoes_ES
renati.jurorReger, Johannes_ES
renati.levelhttps://purl.org/pe-repo/renati/level#maestroes_ES
renati.typehttps://purl.org/pe-repo/renati/type#tesises_ES
dc.publisher.countryPEes_ES
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#2.02.03es_ES


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