Heap Models, Composition and Control

International audienc

Search-based system architecture development using a holistic modeling approach

This dissertation presents an innovative approach to system architecting where search algorithms are used to explore design trade space for good architecture alternatives. Such an approach is achieved by integrating certain model construction, alternative generation, simulation, and assessment processes into a coherent and automated framework. This framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN), and feature model. The resultant holistic model can not only capture the structural, behavioral, and dynamic aspects of a system, allowing simulation and strong analysis methods to be applied, it can also specify the architectural design space. Both object-oriented analysis and design (OOA/D) and domain engineering were exploited to capture design variables and their domains and define architecture generation operations. A fully realized framework (with genetic algorithms as the search algorithm) was developed. Both the proposed framework and its suggested implementation, including the proposed holistic modeling approach and architecture alternative generation operations, are generic. They are targeted at systems that can be specified using object-oriented or process-oriented paradigm. The broad applicability of the proposed approach is demonstrated on two examples. One is the configuration of reconfigurable manufacturing systems (RMSs) under multi-objective optimization and the other is the architecture design of a manned lunar landing system for the Apollo program. The test results show that the proposed approach can cover a huge number of architecture alternatives and support the assessment of several performance measures. A set of quality results was obtained after running the optimization algorithm following the proposed framework --Abstract, page iii

Modeling and formal verification of probabilistic reconfigurable systems

In this thesis, we propose a new approach for formal modeling and verification of adaptive probabilistic systems. Dynamic reconfigurable systems are the trend of all future technological systems, such as flight control systems, vehicle electronic systems, and manufacturing systems. In order to meet user and environmental requirements, such a dynamic reconfigurable system has to actively adjust its configuration at run-time by modifying its components and connections, while changes are detected in the internal/external execution environment. On the other hand, these changes may violate the memory usage, the required energy and the concerned real-time constraints since the behavior of the system is unpredictable. It might also make the system's functions unavailable for some time and make potential harm to human life or large financial investments. Thus, updating a system with any new configuration requires that the post reconfigurable system fully satisfies the related constraints. We introduce GR-TNCES formalism for the optimal functional and temporal specification of probabilistic reconfigurable systems under resource constraints. It enables the optimal specification of a probabilistic, energetic and memory constraints of such a system. To formally verify the correctness and the safety of such a probabilistic system specification, and the non-violation of its properties, an automatic transformation from GR-TNCES models into PRISM models is introduced. Moreover, a new approach XCTL is also proposed to formally verify reconfigurable systems. It enables the formal certification of uncompleted and reconfigurable systems. A new version of the software ZIZO is also proposed to model, simulate and verify such GR-TNCES model. To prove its relevance, the latter was applied to case studies; it was used to model and simulate the behavior of an IPV4 protocol to prevent the energy and memory resources violation. It was also used to optimize energy consumption of an automotive skid conveyor.In dieser Arbeit wird ein neuer Ansatz zur formalen Modellierung und Verifikation dynamisch rekonfigurierbarer Systeme vorgestellt. Dynamische rekonfigurierbare Systeme sind in vielen aktuellen und zukünftigen Anwendungen, wie beispielsweise Flugsteuerungssystemen, Fahrzeugelektronik und Fertigungssysteme zu finden. Diese Systeme weisen ein probabilistisches, adaptives Verhalten auf. Um die Benutzer- und Umgebungsbedingungen kontinuierlich zu erfüllen, muss ein solches System seine Konfiguration zur Laufzeit aktiv anpassen, indem es seine Komponenten, Verbindungen zwischen Komponenten und seine Daten modifiziert (adaptiv), sobald Änderungen in der internen oder externen Ausführungsumgebung erkannt werden (probabilistisch). Diese Anpassungen dürfen Beschränkungen bei der Speichernutzung, der erforderlichen Energie und bestehende Echtzeitbedingungen nicht verletzen. Eine nicht geprüfte Rekonfiguration könnte dazu führen, dass die Funktionen des Systems für einige Zeit nicht verfügbar wären und potenziell menschliches Leben gefährdet würde oder großer finanzieller Schaden entstünde. Somit erfordert das Aktualisieren eines Systems mit einer neuen Konfiguration, dass das rekonfigurierte System die zugehörigen Beschränkungen vollständig einhält. Um dies zu überprüfen, wird in dieser Arbeit der GR-TNCES-Formalismus, eine Erweiterung von Petrinetzen, für die optimale funktionale und zeitliche Spezifikation probabilistischer rekonfigurierbarer Systeme unter Ressourcenbeschränkungen vorgeschlagen. Die entstehenden Modelle sollen über probabilistische model checking verifiziert werden. Dazu eignet sich die etablierte Software PRISM. Um die Verifikation zu ermöglichen wird in dieser Arbeit ein Verfahren zur Transformation von GR-TNCES-Modellen in PRISM-Modelle beschrieben. Eine neu eingeführte Logik (XCTL) erlaubt zudem die einfache Beschreibung der zu prüfenden Eigenschaften. Die genannten Schritte wurden in einer Softwareumgebung für den automatisierten Entwurf, die Simulation und die formale Verifikation (durch eine automatische Transformation nach PRISM) umgesetzt. Eine Fallstudie zeigt die Anwendung des Verfahren

Industrial agents in the era of service-oriented architectures and cloudbased industrial infrastructures

The umbrella paradigm underpinning novel collaborative industrial systems is to consider the set of intelligent system units as a conglomerate of distributed, autonomous, intelligent, proactive, fault-tolerant, and reusable units, which operate as a set of cooperating entities (Colombo and Karnouskos, 2009). These entities are forming an evolvable infrastructure, entering and/or going out (plug-in/plugout) in an asynchronous manner. Moreover, these entities, having each of them their own functionalities, data, and associated information are now connected and able to interact. They are capable of working in a proactive manner, initiating collaborative actions and dynamically interacting with each other in order to achieve both local and global objectives.info:eu-repo/semantics/publishedVersio

Modular supervisory controller for complex systems

Automation for the oil and gas industry is driven by the need to improve efficiency, productivity, consistency, and personnel safety, while reducing cost. Fully automated systems alleviate the physical toll on human operators and allow them to focus on monitoring unsafe well events and machinery maintenance. Complex systems like drilling rigs and snubbing units require supervisory controllers that can safely coordinate equipment and processes, overcome interoperability challenges and allow for functional scalability without sacrificing safety, security, and consistency of operations. The primary objective of this report is to explore the feasibility of developing a modular supervisory controller architecture which addresses these concerns by modifying and extending existing architectures. Such modifications include the use of non-homogeneous models in sub-system modules, including discrete event models for control and physics-based models for collision avoidance, addition of a system compilation module (Meta Module) to identify simple design errors, and implementation of an algorithm for synthesis of modules and filters to replace missing sub-systems. This report discusses the implementation results of the modular supervisory control architecture (modMFSM) on a simplified two-machine drilling system for assessment of design practices. Simulations for three test cases were executed to assess the ability of the controller to correctly perform error-free operations, detect and react to possible collisions, and adapt to missing equipment. The report then discusses the possibilities of extending the modMFSM architecture to control large complex systems such as drilling rigs, using snubbing operations as an example.Mechanical Engineerin

Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

Iterchanging Discrete Event Simulationprocess Interaction Modelsusing The Web Ontology Language - Owl

Discrete event simulation development requires significant investments in time and resources. Descriptions of discrete event simulation models are associated with world views, including the process interaction orientation. Historically, these models have been encoded using high-level programming languages or special purpose, typically vendor-specific, simulation languages. These approaches complicate simulation model reuse and interchange. The current document-centric World Wide Web is evolving into a Semantic Web that communicates information using ontologies. The Web Ontology Language OWL, was used to encode a Process Interaction Modeling Ontology for Discrete Event Simulations (PIMODES). The PIMODES ontology was developed using ontology engineering processes. Software was developed to demonstrate the feasibility of interchanging models from commercial simulation packages using PIMODES as an intermediate representation. The purpose of PIMODES is to provide a vendor-neutral open representation to support model interchange. Model interchange enables reuse and provides an opportunity to improve simulation quality, reduce development costs, and reduce development times

AUTOMATED SYNTHESIS OF VIRTUALBLOCKS FOR INTERFACING SYSTEM UNDER TEST

In this thesis, I/O signal recognizers, called VIRTUALBLOCKS, are synthesized to interface with a SYSTEM UNDER TEST (SUT). Methods for automated synthesis of virtualblocks allow us to simulate environment interfaces with SUT and also perform fault detection on SUT. Such methods must be able to recognize incoming sequences of signals from SUT, and upon the signal recognition determine the proper outgoing sequences of signals to SUT. We characterize our systems into four distinctive systems: system under test, AUXILIARY SYSTEM, controller and external environment. The auxiliary system is represented as a form of condition system Petri net (virtualblocks) and interacts with SUT along with the interaction among the controller and the external environment. Fault detection is performed by subsystems called DETECTBLOCKS synthesized from the virtualblocks. We present construction procedures for virtualblocks andamp; detectblocks and discuss the notion of LEGALITY and DETECTABILITY. Finally, we illustrate our approach using a model of a scanner control unit