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dc.contributor.advisorAvila Ortega, Alfonso
dc.contributor.authorMartinez Esquivel, Rene
dc.creatorAVILA ORTEGA, ALFONSO; 31866
dc.date.accessioned2021-09-26T23:14:30Z
dc.date.available2021-09-26T23:14:30Z
dc.date.created2020-05-10
dc.date.issued2020-05-10
dc.identifier.citationMartínez Esquivel, R. (2020). Dual-core embedded implementation of the SISO adaptive predictive control (Tesis de Maestría). Instituto Tecnológico y de Estudios Superiores de Monterrey. Recuperado de: https://hdl.handle.net/11285/639382es_MX
dc.identifier.urihttps://hdl.handle.net/11285/639382
dc.descriptionFavela Contreras, Antonioes_MX
dc.description.abstractThe SISO Adaptive Predictive Control (APC) algorithm is implemented on a Dual-Core embedded system. The Predictive control strategy is implemented on one of the cores available on the ZYNQ processing system, and the Adaptation Mechanism is implemented on the second core. The implementation can be thought of as two independent applications running simultaneously. However, these are not completely independent. The Predictive Control model is updated on every sampling interval with new parameters generated by the Adaptation mechanism that better fit the response of the system under control. To correctly synchronize the two applications, a Master-Slave architecture was chosen for the communication between the two cores. The core running the predictive control algorithm was assigned the role of the master because it had a longer execution time for every sampling period. This first core acted as the master and orchestrated the flow of data between the two cores and the actions taken by the second core. The second core, which computes the adaptation mechanism, acted as the slave, as it only performed operations when it received a message from the first core at specific times during a sampling period. Further optimization was achieved by using in-line Assembly code, which makes it possible to take advantage of the processor architecture and implement optimal subroutines for a particular application. The low-level optimizations improved execution time by reducing clock cycle counts and reducing the use of external memory for temporary variables. These optimizations resulted in a speedup of up to 3x when compared to the latest embedded implementation of the APC algorithm reported in the literature.es_MX
dc.format.mediumTextoes_MX
dc.language.isoenges_MX
dc.publisherInstituto Tecnológico y de Estudios Superiores de Monterreyes_MX
dc.relation.isFormatOfversión publicadaes_MX
dc.relation.isreferencedbyREPOSITORIO NACIONAL CONACYT
dc.rightsopenAccesses_MX
dc.rights.urihttp://creativecommons.org/about/cc0/es_MX
dc.subject.classificationINGENIERÍA Y TECNOLOGÍA::CIENCIAS TECNOLÓGICAS::TECNOLOGÍA ELECTRÓNICAes_MX
dc.subject.lcshTechnologyes_MX
dc.titleDual-Core embedded implementation of the SISO adaptive predictive controles_MX
dc.typeTrabajo de grado, Maestría / master Degree Workes_MX
dc.contributor.departmentIngeniera Electronicaes_MX
dc.subject.keywordEmbeddedes_MX
dc.subject.keywordDual-Corees_MX
dc.subject.keywordAPC SISO Controles_MX
dc.contributor.institutionCampus Monterreyes_MX
dc.contributor.catalogertolmquevedo, emipsanchezes_MX
dc.description.degreeMaestriaes_MX
dc.audience.educationlevelInvestigadores/Researcherses_MX
dc.relation.impreso2020-05-08
dc.identificator7||33||3307es_MX


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