7 research outputs found

    Exploring Architectural Model Checking with Declarative Specifications

    Get PDF
    In this work we explore the FVS language in the context of architectural behavior model checking. FVS holds desirable characteristics for this particular domain. Its flexible notation enables the possibility of performing behavioral exploration when denoting the properties to be satisfied. In addition, FVS expressive power capable of denoting ω-regular properties is useful to denote behavior in a higher level of abstraction. These are two key activities when specifying and validating a system architecture. Given that FVS specifications can be translated into B¨uchi automata they can be used as input in a validation tool like model checkers. In this sense, we conducted industrial relevant case studies to apply our approach in concrete examples.XIV Workshop de Ingeniería de Software (WIS).Red de Universidades con Carreras en Informática (RedUNCI

    Real-time multi-domain optimization controller for multi-motor electric vehicles using automotive-suitable methods and heterogeneous embedded platforms

    Get PDF
    Los capítulos 2,3 y 7 están sujetos a confidencialidad por el autor. 145 p.In this Thesis, an elaborate control solution combining Machine Learning and Soft Computing techniques has been developed, targeting a chal lenging vehicle dynamics application aiming to optimize the torque distribution across the wheels with four independent electric motors.The technological context that has motivated this research brings together potential -and challenges- from multiple dom ains: new automotive powertrain topologies with increased degrees of freedom and controllability, which can be approached with innovative Machine Learning algorithm concepts, being implementable by exploiting the computational capacity of modern heterogeneous embedded platforms and automated toolchains. The complex relations among these three domains that enable the potential for great enhancements, do contrast with the fourth domain in this context: challenging constraints brought by industrial aspects and safe ty regulations. The innovative control architecture that has been conce ived combines Neural Networks as Virtual Sensor for unmeasurable forces , with a multi-objective optimization function driven by Fuzzy Logic , which defines priorities basing on the real -time driving situation. The fundamental principle is to enhance vehicle dynamics by implementing a Torque Vectoring controller that prevents wheel slip using the inputs provided by the Neural Network. Complementary optimization objectives are effici ency, thermal stress and smoothness. Safety -critical concerns are addressed through architectural and functional measures.Two main phases can be identified across the activities and milestones achieved in this work. In a first phase, a baseline Torque Vectoring controller was implemented on an embedded platform and -benefiting from a seamless transition using Hardware-in -the -Loop - it was integrated into a real Motor -in -Wheel vehicle for race track tests. Having validated the concept, framework, methodology and models, a second simulation-based phase proceeds to develop the more sophisticated controller, targeting a more capable vehicle, leading to the final solution of this work. Besides, this concept was further evolved to support a joint research work which lead to outstanding FPGA and GPU based embedded implementations of Neural Networks. Ultimately, the different building blocks that compose this work have shown results that have met or exceeded the expectations, both on technical and conceptual level. The highly non-linear multi-variable (and multi-objective) control problem was tackled. Neural Network estimations are accurate, performance metrics in general -and vehicle dynamics and efficiency in particular- are clearly improved, Fuzzy Logic and optimization behave as expected, and efficient embedded implementation is shown to be viable. Consequently, the proposed control concept -and the surrounding solutions and enablers- have proven their qualities in what respects to functionality, performance, implementability and industry suitability.The most relevant contributions to be highlighted are firstly each of the algorithms and functions that are implemented in the controller solutions and , ultimately, the whole control concept itself with the architectural approaches it involves. Besides multiple enablers which are exploitable for future work have been provided, as well as an illustrative insight into the intricacies of a vivid technological context, showcasing how they can be harmonized. Furthermore, multiple international activities in both academic and professional contexts -which have provided enrichment as well as acknowledgement, for this work-, have led to several publications, two high-impact journal papers and collateral work products of diverse nature

    Real-time multi-domain optimization controller for multi-motor electric vehicles using automotive-suitable methods and heterogeneous embedded platforms

    Get PDF
    Los capítulos 2,3 y 7 están sujetos a confidencialidad por el autor. 145 p.In this Thesis, an elaborate control solution combining Machine Learning and Soft Computing techniques has been developed, targeting a chal lenging vehicle dynamics application aiming to optimize the torque distribution across the wheels with four independent electric motors.The technological context that has motivated this research brings together potential -and challenges- from multiple dom ains: new automotive powertrain topologies with increased degrees of freedom and controllability, which can be approached with innovative Machine Learning algorithm concepts, being implementable by exploiting the computational capacity of modern heterogeneous embedded platforms and automated toolchains. The complex relations among these three domains that enable the potential for great enhancements, do contrast with the fourth domain in this context: challenging constraints brought by industrial aspects and safe ty regulations. The innovative control architecture that has been conce ived combines Neural Networks as Virtual Sensor for unmeasurable forces , with a multi-objective optimization function driven by Fuzzy Logic , which defines priorities basing on the real -time driving situation. The fundamental principle is to enhance vehicle dynamics by implementing a Torque Vectoring controller that prevents wheel slip using the inputs provided by the Neural Network. Complementary optimization objectives are effici ency, thermal stress and smoothness. Safety -critical concerns are addressed through architectural and functional measures.Two main phases can be identified across the activities and milestones achieved in this work. In a first phase, a baseline Torque Vectoring controller was implemented on an embedded platform and -benefiting from a seamless transition using Hardware-in -the -Loop - it was integrated into a real Motor -in -Wheel vehicle for race track tests. Having validated the concept, framework, methodology and models, a second simulation-based phase proceeds to develop the more sophisticated controller, targeting a more capable vehicle, leading to the final solution of this work. Besides, this concept was further evolved to support a joint research work which lead to outstanding FPGA and GPU based embedded implementations of Neural Networks. Ultimately, the different building blocks that compose this work have shown results that have met or exceeded the expectations, both on technical and conceptual level. The highly non-linear multi-variable (and multi-objective) control problem was tackled. Neural Network estimations are accurate, performance metrics in general -and vehicle dynamics and efficiency in particular- are clearly improved, Fuzzy Logic and optimization behave as expected, and efficient embedded implementation is shown to be viable. Consequently, the proposed control concept -and the surrounding solutions and enablers- have proven their qualities in what respects to functionality, performance, implementability and industry suitability.The most relevant contributions to be highlighted are firstly each of the algorithms and functions that are implemented in the controller solutions and , ultimately, the whole control concept itself with the architectural approaches it involves. Besides multiple enablers which are exploitable for future work have been provided, as well as an illustrative insight into the intricacies of a vivid technological context, showcasing how they can be harmonized. Furthermore, multiple international activities in both academic and professional contexts -which have provided enrichment as well as acknowledgement, for this work-, have led to several publications, two high-impact journal papers and collateral work products of diverse nature

    Explicitly Integrated Architecture - An Approach for Integrating Software Architecture Model Information with Program Code

    Get PDF
    Software-Architekturspezifikationen und -Implementierungen sind zwei Sichtweisen auf Softwarearchitektur. Sie beschreiben gemeinsame Aspekte, wie z.B. die Existenz und Verbindung von Komponenten. Die Spezifikation fügt Informationen zum Design, zur Kommunikation und zur Analyse hinzu. Die Implementierung beschreibt stattdessen zusätzlich Details für ein ausführbares System. Die Konsistenz zwischen diesen Darstellungen manuell zu verwalten, ist schwierig und fehleranfällig. Diese Arbeit stellt einen Ansatz vor, der Informationen der Architekturspezifikation vollständig in die Implementierung integriert, sodass die Spezifikation als eigenständiges Artefakt nicht mehr notwendig ist. Das Tool Codeling extrahiert die integrierte Architekturspezifikation in unterschiedlichen Sprachen aus dem Code und propagiert Änderungen in dieser Spezifikation automatisch an den Code zurück.Specifications and implementations are both viewpoints upon software architecture. Besides common aspects, the specification adds information for design, communication, or analysis, while the implementation adds details for an executable system instead. Managing the consistency between these representations manually is difficult and error-prone. This thesis presents an approach, that completely integrates architecture specifications with the implementation, so that separate specification artifacts are not necessary anymore. The tool Codeling extracts integrated architecture specifications in multiple languages from code, and automatically propagates changes in these specifications back to the code

    XXIII Congreso Argentino de Ciencias de la Computación - CACIC 2017 : Libro de actas

    Get PDF
    Trabajos presentados en el XXIII Congreso Argentino de Ciencias de la Computación (CACIC), celebrado en la ciudad de La Plata los días 9 al 13 de octubre de 2017, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Informática de la Universidad Nacional de La Plata (UNLP).Red de Universidades con Carreras en Informática (RedUNCI

    Specifying Architecture Behavior with SysADL

    No full text
    International audienceSysADL is a SysML profile for describing architectures using the well-known and consolidated abstractions from the software architecture community. It defines a systematic use of SysML specifically supporting architecture descriptions. For this purpose, it encompasses three integrated viewpoints: structural, behavioral, and executable. This paper focuses on the behavioral viewpoint that relies on the SysML activity and parametric diagrams to capture the behavior of atomic and composite architectural elements. We use an air-conditioning systems as a case study to illustrate SysADL behavioral views and investigate the applicability of SysADL through a controlled experiment
    corecore