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dc.contributor.advisorVilla, José Luisspa
dc.contributor.authorPeña Borrero, Carlos Albertospa
dc.contributor.authorUlloa Candanoza, Jorge Luisspa
dc.contributor.authorRamírez Hamburger, Carlos Enriquespa
dc.contributor.authorPertuz Rudas, Erwin Enriquespa
dc.contributor.authorDavid, María del Socorrospa
dc.date.accessioned2020-06-26T21:32:19Z
dc.date.available2020-06-26T21:32:19Z
dc.date.issued2007
dc.identifier.urihttp://hdl.handle.net/20.500.12749/3324
dc.description.abstractEl principal objetivo del proyecto fue implementar un programa para validar la correcta definición de un sistema dinámico híbrido, representado con un modelo MLD (Mixed Logical and Dynamic System), por lo que el principal aporte del mismo consiste en implementar un algoritmo de validación del modelo MLD, que le permite al diseñador visualizar gráficamente el campo vectorial del sistema. El trabajo incluye una definición de las características de un sistema bien definido, y de lo que se entiende como un sistema mal definido, con lo cual se establecen las especificaciones del algoritmo para dar solución al objetivo especifico de determinar las características de funcionamiento del algoritmo de validación. El algoritmo implementado se basa en la teoría propuesta por Bemporad y Morari; esto constituye la solución del objetivo de implementar y evaluar el algoritmo MILP (Programación Lineal Entera Mixta) con un problema de ejemplo MLD. Debido al alto costo computacional que el algoritmo propuesto presenta, se desarrolla y propone una versión utilizando computación distribuida, con lo cual la solución propuesta resulta de mayor utilidad, dando de esta forma solución al objetivo especifico de proponer un algoritmo mejorado que reduzca el tiempo de computación en el problema MLD. Ambos algoritmos se aplican a tres casos de estudio donde se evalúan los ajustes de parámetros del algoritmo y su respectivo tiempo de ejecución, dando solución al objetivo específico de evaluar el comportamiento del algoritmo propuesto en un problema de estudio. Finalmente con esta aproximación se logra una mejora significativa en los tiempos de ejecución del algoritmo a través de la programación distribuida, se cambia la plataforma de procesamiento y se trabaja con esta filosofía, obteniendo los mismos resultados con una significativa disminución del tiempo de ejecución de dicho algoritmo, en cada uno de los casos.spa
dc.description.tableofcontentsLISTA DE FIGURAS............................................................................................................8 LISTA DE TABLAS............................................................................................................10 LISTA DE ALGORITMOS.................................................................................................11 LISTA DE ANEXOS...........................................................................................................12 1. INTRODUCCION......................................................................................................13 2. SISTEMAS LOGICOS Y DINAMICOS MIXTOS - MLD (MIXED LOGICAL AND DYNAMICAL)...........................................................................................................16 2.1 GENERALIDADES DE SISTEMAS DINAMICOS..........................................16 2.2 EL MODELO MLD ...........................................................................................20 2.3 Equivalencia entre representaciones de Sistemas Híbridos.................................23 2.4 HERRAMIENTAS DE ANALISIS PARA SISTEMAS MLD...........................24 2.4.1 Hysdel (Hybrid System Description Language)..................................................25 2.4.2 Matlab (Matrix laboratory)..................................................................................26 3. CASOS DE ESTUDIO DE SISTEMAS MLD..........................................................29 3.1 DEFINICION FORMAL DE SISTEMAS MLD CORRECTAMENTE DEFINIDOS..................................................................................................................29 3.2 CASOS DE ESTUDIO........................................................................................30 3.2.1 Caso 1 Modelo de un Sistema Bien Definido......................................................31 3.2.2 Caso 2 Modelo de un sistema sin condición de existencia (ausencia de solución) 34 3.2.3 Caso 3 Modelo de un sistema sin condición de unicidad (soluciones múltiples)37 4. ALGORITMO DE VALIDACIÓN............................................................................40 4.1 EL ALGORITMO DE VALIDACIÓN......................................................................40 7 4.1.1 Existencia de soluciones......................................................................................40 4.1.2 Unicidad de soluciones........................................................................................42 4.2 METODO BRANCH & BOUND..............................................................................44 4.3 RESULTADOS Y ANÁLISIS DE RESULTADOS..................................................50 4.4 Complejidad Computacional......................................................................................64 5. ALGORITMO DE VALIDACIÓN CON COMPUTACIÓN DISTRIBUIDA........65 5.1 SOLUCION CON ALGORITMO DISTRIBUIDO IMPLEMENTADO EN JAVA 66 5.2 ALGORITMO FINAL DE VALIDACIÓN BASADO EN COMPUTACIÓN DISTRIBUIDA.....................................................................................................................68 5.3 RESULTADOS Y ANÁLISIS DE RESULTADOS..................................................69 5.3.1 CASO 1. Modelo de un sistema bien definido....................................................69 5.3.2 CASO 2. Modelo de un sistema sin condición de existencia (Ausencia de solución) 70 5.3.3 CASO 3. Modelo de un sistema sin condición de Unicidad (Soluciones Múltiples)72 5.4 COMPLEJIDAD COMPUTACIONAL DEL ALGORITMO DISTRIBUIDO........74 6. CONCLUSIONES Y TRABAJOS FUTUROS........................................................75 6.1 CONCLUSIONES......................................................................................................75 6.2 TRABAJOS FUTUROS.............................................................................................76 BIBLIOGRAFÍA........................................................................................................78 ANEXOS..............................................................................................................................84spa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/*
dc.titleValidación de la correcta definición del modelo de un sistema híbrido representado en MLDspa
dc.title.translatedValidation of the correct definition of the model of a hybrid system represented in MLDeng
dc.degree.nameMagíster en Ciencias Computacionalesspa
dc.coverageBucaramanga (Colombia)spa
dc.publisher.grantorUniversidad Autónoma de Bucaramanga UNABspa
dc.rights.localAbierto (Texto Completo)spa
dc.publisher.facultyFacultad Ingenieríaspa
dc.publisher.programMaestría en Ciencias Computacionalesspa
dc.description.degreelevelMaestríaspa
dc.type.driverinfo:eu-repo/semantics/masterThesis
dc.type.localTesisspa
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcc
dc.subject.keywordsHybrid systemseng
dc.subject.keywordsElectronic data processingeng
dc.subject.keywordsDifferential dynamic systemseng
dc.subject.keywordsSystems Engineeringeng
dc.subject.keywordsComputer scienceeng
dc.subject.keywordsDistributed treatmenteng
dc.subject.keywordsInvestigationseng
dc.subject.keywordsAnalysiseng
dc.subject.keywordsMLD modeleng
dc.subject.keywordsAlgorithmeng
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga - UNABspa
dc.identifier.reponamereponame:Repositorio Institucional UNABspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2spa
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dc.relation.referencesCharon, Deparment of Computer and Information Science, University of Pennsylvania. http://www.cis.upenn.edu/mobies/charonspa
dc.relation.referencesAn overview of hybrid simulation phenomena and their support by simulation packages. P. Mosterman. http://robotics.eecs.berkeley.edu/~sastry/ee291e/mosterman.pdfspa
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dc.relation.referencesThe Hybrid Systems Group. http://control.ee.ethz.ch/~hybridspa
dc.contributor.cvlachttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000054038*
dc.subject.lembSistemas híbridosspa
dc.subject.lembProcesamiento electrónico de datosspa
dc.subject.lembSistemas dinámicos diferencialesspa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembCiencias computacionalesspa
dc.subject.lembTratamiento distribuidospa
dc.subject.lembInvestigacionesspa
dc.subject.lembAnálisisspa
dc.contributor.corporatenameInstituto Tecnológico y de Estudios Superiores de Monterrey (ITESM)spa
dc.description.abstractenglishThe main objective of the project was to implement a program to validate the correct definition of a hybrid dynamic system, represented with an MLD (Mixed Logical and Dynamic System) model, so its main contribution consists in implementing a model validation algorithm MLD, which allows the designer to graphically visualize the vector field of the system. The work includes a definition of the characteristics of a well-defined system, and of what is understood as a poorly defined system, which establishes the specifications of the algorithm to solve the specific objective of determining the operating characteristics of the algorithm of validation. The implemented algorithm is based on the theory proposed by Bemporad and Morari; this constitutes the solution of the objective of implementing and evaluating the MILP (Mixed Integer Linear Programming) algorithm with an example MLD problem. Due to the high computational cost that the proposed algorithm presents, a version is developed and proposed using distributed computing, with which the proposed solution is more useful, thus providing a solution to the specific objective of proposing an improved algorithm that reduces the time of computation in the MLD problem. Both algorithms are applied to three study cases where the parameter settings of the algorithm and their respective execution time are evaluated, providing a solution to the specific objective of evaluating the behavior of the algorithm proposed in a study problem. Finally, with this approach, a significant improvement in algorithm execution times is achieved through distributed programming, the processing platform is changed and this philosophy is used, obtaining the same results with a significant decrease in the execution time of said algorithm. algorithm, in each of the cases.eng
dc.subject.proposalModelo MLD
dc.subject.proposalAlgoritmo
dc.type.redcolhttp://purl.org/redcol/resource_type/TM
dc.rights.creativecommonsAtribución-NoComercial-SinDerivadas 2.5 Colombia*
dc.coverage.campusUNAB Campus Bucaramangaspa
dc.description.learningmodalityModalidad Presencialspa


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