Submitted by Gilmar Barros (gilmargomesdebarros@gmail.com) on 2015-05-12T17:00:56Z No. of bitstreams: 1 Tese - Rafael Penna.pdf: 5494264 bytes, checksum: 3a53496319b33a5169c281e0bcb7a800 (MD5) / Rejected by Vitor de Carvalho (vitor_carvalho_im@hotmail.com), reason: - Sobrenomes de autor/orientador não podem estar em caixa alta; - Falta um dos sobrenomes da orientadora. on 2015-06-12T19:44:55Z (GMT) / Submitted by Gilmar Barros (gilmargomesdebarros@gmail.com) on 2015-06-15T15:33:55Z No. of bitstreams: 1 Tese - Rafael Penna.pdf: 5494264 bytes, checksum: 3a53496319b33a5169c281e0bcb7a800 (MD5) / Approved for entry into archive by Vitor de Carvalho (vitor_carvalho_im@hotmail.com) on 2015-06-22T18:57:30Z (GMT) No. of bitstreams: 1 Tese - Rafael Penna.pdf: 5494264 bytes, checksum: 3a53496319b33a5169c281e0bcb7a800 (MD5) / Made available in DSpace on 2015-06-22T18:57:30Z (GMT). No. of bitstreams: 1 Tese - Rafael Penna.pdf: 5494264 bytes, checksum: 3a53496319b33a5169c281e0bcb7a800 (MD5) Previous issue date: 2014 / O avanço tecnológico dos últimos anos ocasionou mudanças na maneira como as pessoas se relacionam. Dispositivos computacionais, sensores e atuadores se fazem presentes na vida das pessoas atualmente, de maneira que os mundos físico e virtual se misturam. Propostas de sistemas físico-cibernéticos (Cyber-Physical Systems ou CPS) surgem com o intuito de integrar os sistemas computacionais com objetos do mundo físico. Neste novo contexto, as discussões dos impactos tecnológicos nos ambientes escolares são importante, estabelecendo novas áreas de pesquisa, como ensino eletrônico, educação à distância, aprendizagem móvel e aprendizagem ubíqua. Dentro dessas áreas, os Ambientes Virtuais de Aprendizagem (AVAs), que são sistemas computacionais disponíveis na internet, destinados ao suporte de atividades mediadas pelas tecnologias de informação e comunicação, são bastante utilizados e estudados. Esses ambientes podem ser identificados por uma série de características que envolvem interação entre alunos e professores, oportunidades de socialização e concepção de informação, propostas pedagógicas, representação do espaço virtual, entre outras. No entanto, os AVAs costumam apresentar possibilidades restritas de lidar com as informações do mundo físico. Esta tese tem como foco a integração de elementos reais/físicos em AVAs, através de interfaces humano-computador avançadas. Para tanto, propõe-se a definição de Ambientes Físico- Virtuais de Aprendizagem, discutindo suas características e um modelo conceitual de referência. Por fim, a plataforma Toogle, proposta para implementação de sistemas físicocibernéticos, é aprimorada e utilizada no desenvolvimento desses novos espaços. / Technological advances in recent years has brought about changes in the way people relate. Computing devices, sensors and actuators are present in the in people's lives today, in a way that the physical and virtual worlds mix. Proposals of Cyber-Physical Systems (CPS) arise in order to integrate computer systems with the physical world objects.In this new context, discussions about technological impacts on school environments are important, establishing new areas of research, such as e-learning, distance education, mobile learning and ubiquitous learning. Within these areas, the Virtual Learning Environments (VLEs), which are computer systems available on the Internet, intended to support activities mediated by information and communication technologies, are widely used and studied. These environments can be identified by a number of features that involve interaction between students and teachers, socialization opportunities, educational proposals, representation of virtual space, among others. However, VLEs often have limited possibilities to deal with the information of the physical world. This dissertation focuses on the integration of real / physical elements in VLEs, through advanced human-computer interfaces. We propose the definition of Cyber-Physical Learning Environments, discussing their characteristics and a reference conceptual model. Finally, the Toogle plataform, proposed to implement cyber-physical systems, is enhanced and used to develop these new spaces.

More and more of our physical world today is being monitored and controlled by so-called cyber-physical systems (CPSs). These are compositions of networked autonomous cyber and physical agents such as sensors, actuators, computational elements, and humans in the loop. Today, CPSs are still relatively small-scale and very limited compared to CPSs to be witnessed in the future. Future CPSs are expected to be far more complex, large-scale, wide-spread, and mission-critical, and found in a variety of domains such as transportation, medicine, manufacturing, and energy, where they will bring many advantages such as the increased efficiency, sustainability, reliability, and security. To unleash their full potential, CPSs need to be equipped with, among other features, the support for automated planning and control, where computing agents collaboratively and continuously plan and control their actions in an intelligent and well-coordinated manner to secure and optimize a physical process, e.g., electricity flow in the power grid. In today’s CPSs, the control is typically automated, but the planning is solely performed by humans. Unfortunately, it is intractable and infeasible for humans to plan every action in a future CPS due to the complexity, scale, and volatility of a physical process. Due to these properties, the control and planning has to be continuous and automated in future CPSs. Humans may only analyse and tweak the system’s operation using the set of tools supporting prescriptive analytics that allows them (1) to make predictions, (2) to get the suggestions of the most prominent set of actions (decisions) to be taken, and (3) to analyse the implications as if such actions were taken. This thesis considers the planning and control in the context of a large-scale multi-agent CPS. Based on the smart-grid use-case, it presents a so-called PrescriptiveCPS – which is (the conceptual model of) a multi-agent, multi-role, and multi-level CPS automatically and continuously taking and realizing decisions in near real-time and providing (human) users prescriptive analytics tools to analyse and manage the performance of the underlying physical system (or process). Acknowledging the complexity of CPSs, this thesis provides contributions at the following three levels of scale: (1) the level of a (full) PrescriptiveCPS, (2) the level of a single PrescriptiveCPS agent, and (3) the level of a component of a CPS agent software system. At the CPS level, the contributions include the definition of PrescriptiveCPS, according to which it is the system of interacting physical and cyber (sub-)systems. Here, the cyber system consists of hierarchically organized inter-connected agents, collectively managing instances of so-called flexibility, decision, and prescription models, which are short-lived, focus on the future, and represent a capability, an (user’s) intention, and actions to change the behaviour (state) of a physical system, respectively. At the agent level, the contributions include the three-layer architecture of an agent software system, integrating the number of components specially designed or enhanced to support the functionality of PrescriptiveCPS. At the component level, the most of the thesis contribution is provided. The contributions include the description, design, and experimental evaluation of (1) a unified multi-dimensional schema for storing flexibility and prescription models (and related data), (2) techniques to incrementally aggregate flexibility model instances and disaggregate prescription model instances, (3) a database management system (DBMS) with built-in optimization problem solving capability allowing to formulate optimization problems using SQL-like queries and to solve them “inside a database”, (4) a real-time data management architecture for processing instances of flexibility and prescription models under (soft or hard) timing constraints, and (5) a graphical user interface (GUI) to visually analyse the flexibility and prescription model instances. Additionally, the thesis discusses and exemplifies (but provides no evaluations of) (1) domain-specific and in-DBMS generic forecasting techniques allowing to forecast instances of flexibility models based on historical data, and (2) powerful ways to analyse past, current, and future based on so-called hypothetical what-if scenarios and flexibility and prescription model instances stored in a database. Most of the contributions at this level are based on the smart-grid use-case. In summary, the thesis provides (1) the model of a CPS with planning capabilities, (2) the design and experimental evaluation of prescriptive analytics techniques allowing to effectively forecast, aggregate, disaggregate, visualize, and analyse complex models of the physical world, and (3) the use-case from the energy domain, showing how the introduced concepts are applicable in the real world. We believe that all this contribution makes a significant step towards developing planning-capable CPSs in the future. / Mehr und mehr wird heute unsere physische Welt überwacht und durch sogenannte Cyber-Physical-Systems (CPS) geregelt. Dies sind Kombinationen von vernetzten autonomen cyber und physischen Agenten wie Sensoren, Aktoren, Rechenelementen und Menschen. Heute sind CPS noch relativ klein und im Vergleich zu CPS der Zukunft sehr begrenzt. Zukünftige CPS werden voraussichtlich weit komplexer, größer, weit verbreiteter und unternehmenskritischer sein sowie in einer Vielzahl von Bereichen wie Transport, Medizin, Fertigung und Energie – in denen sie viele Vorteile wie erhöhte Effizienz, Nachhaltigkeit, Zuverlässigkeit und Sicherheit bringen – anzutreffen sein. Um ihr volles Potenzial entfalten zu können, müssen CPS unter anderem mit der Unterstützung automatisierter Planungs- und Steuerungsfunktionalität ausgestattet sein, so dass Agents ihre Aktionen gemeinsam und kontinuierlich auf intelligente und gut koordinierte Weise planen und kontrollieren können, um einen physischen Prozess wie den Stromfluss im Stromnetz sicherzustellen und zu optimieren. Zwar sind in den heutigen CPS Steuerung und Kontrolle typischerweise automatisiert, aber die Planung wird weiterhin allein von Menschen durchgeführt. Leider ist diese Aufgabe nur schwer zu bewältigen, und es ist für den Menschen schlicht unmöglich, jede Aktion in einem zukünftigen CPS auf Basis der Komplexität, des Umfangs und der Volatilität eines physikalischen Prozesses zu planen. Aufgrund dieser Eigenschaften müssen Steuerung und Planung in CPS der Zukunft kontinuierlich und automatisiert ablaufen. Der Mensch soll sich dabei ganz auf die Analyse und Einflussnahme auf das System mit Hilfe einer Reihe von Werkzeugen konzentrieren können. Derartige Werkzeuge erlauben (1) Vorhersagen, (2) Vorschläge der wichtigsten auszuführenden Aktionen (Entscheidungen) und (3) die Analyse und potentiellen Auswirkungen der zu fällenden Entscheidungen. Diese Arbeit beschäftigt sich mit der Planung und Kontrolle im Rahmen großer Multi-Agent-CPS. Basierend auf dem Smart-Grid als Anwendungsfall wird ein sogenanntes PrescriptiveCPS vorgestellt, welches einem Multi-Agent-, Multi-Role- und Multi-Level-CPS bzw. dessen konzeptionellem Modell entspricht. Diese PrescriptiveCPS treffen und realisieren automatisch und kontinuierlich Entscheidungen in naher Echtzeit und stellen Benutzern (Menschen) Prescriptive-Analytics-Werkzeuge und Verwaltung der Leistung der zugrundeliegenden physischen Systeme bzw. Prozesse zur Verfügung. In Anbetracht der Komplexität von CPS leistet diese Arbeit Beiträge auf folgenden Ebenen: (1) Gesamtsystem eines PrescriptiveCPS, (2) PrescriptiveCPS-Agenten und (3) Komponenten eines CPS-Agent-Software-Systems. Auf CPS-Ebene umfassen die Beiträge die Definition von PrescriptiveCPS als ein System von wechselwirkenden physischen und cyber (Sub-)Systemen. Das Cyber-System besteht hierbei aus hierarchisch organisierten verbundenen Agenten, die zusammen Instanzen sogenannter Flexibility-, Decision- und Prescription-Models verwalten, welche von kurzer Dauer sind, sich auf die Zukunft konzentrieren und Fähigkeiten, Absichten (des Benutzers) und Aktionen darstellen, die das Verhalten des physischen Systems verändern. Auf Agenten-Ebene umfassen die Beiträge die Drei-Ebenen-Architektur eines Agentensoftwaresystems sowie die Integration von Komponenten, die insbesondere zur besseren Unterstützung der Funktionalität von PrescriptiveCPS entwickelt wurden. Der Schwerpunkt dieser Arbeit bilden die Beiträge auf der Komponenten-Ebene, diese umfassen Beschreibung, Design und experimentelle Evaluation (1) eines einheitlichen multidimensionalen Schemas für die Speicherung von Flexibility- and Prescription-Models (und verwandten Daten), (2) der Techniken zur inkrementellen Aggregation von Instanzen eines Flexibilitätsmodells und Disaggregation von Prescription-Models, (3) eines Datenbankmanagementsystem (DBMS) mit integrierter Optimierungskomponente, die es erlaubt, Optimierungsprobleme mit Hilfe von SQL-ähnlichen Anfragen zu formulieren und sie „in einer Datenbank zu lösen“, (4) einer Echtzeit-Datenmanagementarchitektur zur Verarbeitung von Instanzen der Flexibility- and Prescription-Models unter (weichen oder harten) Zeitvorgaben und (5) einer grafische Benutzeroberfläche (GUI) zur Visualisierung und Analyse von Instanzen der Flexibility- and Prescription-Models. Darüber hinaus diskutiert und veranschaulicht diese Arbeit beispielhaft ohne detaillierte Evaluation (1) anwendungsspezifische und im DBMS integrierte Vorhersageverfahren, die die Vorhersage von Instanzen der Flexibility- and Prescription-Models auf Basis historischer Daten ermöglichen, und (2) leistungsfähige Möglichkeiten zur Analyse von Vergangenheit, Gegenwart und Zukunft auf Basis sogenannter hypothetischer „What-if“-Szenarien und der in der Datenbank hinterlegten Instanzen der Flexibility- and Prescription-Models. Die meisten der Beiträge auf dieser Ebene basieren auf dem Smart-Grid-Anwendungsfall. Zusammenfassend befasst sich diese Arbeit mit (1) dem Modell eines CPS mit Planungsfunktionen, (2) dem Design und der experimentellen Evaluierung von Prescriptive-Analytics-Techniken, die eine effektive Vorhersage, Aggregation, Disaggregation, Visualisierung und Analyse komplexer Modelle der physischen Welt ermöglichen und (3) dem Anwendungsfall der Energiedomäne, der zeigt, wie die vorgestellten Konzepte in der Praxis Anwendung finden. Wir glauben, dass diese Beiträge einen wesentlichen Schritt in der zukünftigen Entwicklung planender CPS darstellen. / Mere og mere af vores fysiske verden bliver overvåget og kontrolleret af såkaldte cyber-fysiske systemer (CPSer). Disse er sammensætninger af netværksbaserede autonome IT (cyber) og fysiske (physical) agenter, såsom sensorer, aktuatorer, beregningsenheder, og mennesker. I dag er CPSer stadig forholdsvis små og meget begrænsede i forhold til de CPSer vi kan forvente i fremtiden. Fremtidige CPSer forventes at være langt mere komplekse, storstilede, udbredte, og missionskritiske, og vil kunne findes i en række områder såsom transport, medicin, produktion og energi, hvor de vil give mange fordele, såsom øget effektivitet, bæredygtighed, pålidelighed og sikkerhed. For at frigøre CPSernes fulde potentiale, skal de bl.a. udstyres med støtte til automatiseret planlægning og kontrol, hvor beregningsagenter i samspil og løbende planlægger og styrer deres handlinger på en intelligent og velkoordineret måde for at sikre og optimere en fysisk proces, såsom elforsyningen i elnettet. I nuværende CPSer er styringen typisk automatiseret, mens planlægningen udelukkende er foretaget af mennesker. Det er umuligt for mennesker at planlægge hver handling i et fremtidigt CPS på grund af kompleksiteten, skalaen, og omskifteligheden af en fysisk proces. På grund af disse egenskaber, skal kontrol og planlægning være kontinuerlig og automatiseret i fremtidens CPSer. Mennesker kan kun analysere og justere systemets drift ved hjælp af det sæt af værktøjer, der understøtter præskriptive analyser (prescriptive analytics), der giver dem mulighed for (1) at lave forudsigelser, (2) at få forslagene fra de mest fremtrædende sæt handlinger (beslutninger), der skal tages, og (3) at analysere konsekvenserne, hvis sådanne handlinger blev udført. Denne afhandling omhandler planlægning og kontrol i forbindelse med store multi-agent CPSer. Baseret på en smart-grid use case, præsenterer afhandlingen det såkaldte PrescriptiveCPS hvilket er (den konceptuelle model af) et multi-agent, multi-rolle, og multi-level CPS, der automatisk og kontinuerligt tager beslutninger i nær-realtid og leverer (menneskelige) brugere præskriptiveanalyseværktøjer til at analysere og håndtere det underliggende fysiske system (eller proces). I erkendelse af kompleksiteten af CPSer, giver denne afhandling bidrag til følgende tre niveauer: (1) niveauet for et (fuldt) PrescriptiveCPS, (2) niveauet for en enkelt PrescriptiveCPS agent, og (3) niveauet for en komponent af et CPS agent software system. På CPS-niveau, omfatter bidragene definitionen af PrescriptiveCPS, i henhold til hvilken det er det system med interagerende fysiske- og IT- (under-) systemer. Her består IT-systemet af hierarkisk organiserede forbundne agenter der sammen styrer instanser af såkaldte fleksibilitet (flexibility), beslutning (decision) og præskriptive (prescription) modeller, som henholdsvis er kortvarige, fokuserer på fremtiden, og repræsenterer en kapacitet, en (brugers) intention, og måder til at ændre adfærd (tilstand) af et fysisk system. På agentniveau omfatter bidragene en tre-lags arkitektur af et agent software system, der integrerer antallet af komponenter, der er specielt konstrueret eller udbygges til at understøtte funktionaliteten af PrescriptiveCPS. Komponentniveauet er hvor afhandlingen har sit hovedbidrag. Bidragene omfatter beskrivelse, design og eksperimentel evaluering af (1) et samlet multi- dimensionelt skema til at opbevare fleksibilitet og præskriptive modeller (og data), (2) teknikker til trinvis aggregering af fleksibilitet modelinstanser og disaggregering af præskriptive modelinstanser (3) et database management system (DBMS) med indbygget optimeringsproblemløsning (optimization problem solving) der gør det muligt at formulere optimeringsproblemer ved hjælp af SQL-lignende forespørgsler og at løse dem "inde i en database", (4) en realtids data management arkitektur til at behandle instanser af fleksibilitet og præskriptive modeller under (bløde eller hårde) tidsbegrænsninger, og (5) en grafisk brugergrænseflade (GUI) til visuelt at analysere fleksibilitet og præskriptive modelinstanser. Derudover diskuterer og eksemplificerer afhandlingen (men giver ingen evalueringer af) (1) domæne-specifikke og in-DBMS generiske prognosemetoder der gør det muligt at forudsige instanser af fleksibilitet modeller baseret på historiske data, og (2) kraftfulde måder at analysere tidligere-, nutids- og fremtidsbaserede såkaldte hypotetiske hvad-hvis scenarier og fleksibilitet og præskriptive modelinstanser gemt i en database. De fleste af bidragene på dette niveau er baseret på et smart-grid brugsscenarie. Sammenfattende giver afhandlingen (1) modellen for et CPS med planlægningsmulighed, (2) design og eksperimentel evaluering af præskriptive analyse teknikker der gør det muligt effektivt at forudsige, aggregere, disaggregere, visualisere og analysere komplekse modeller af den fysiske verden, og (3) brugsscenariet fra energiområdet, der viser, hvordan de indførte begreber kan anvendes i den virkelige verden. Vi mener, at dette bidrag udgør et betydeligt skridt i retning af at udvikle CPSer til planlægningsbrug i fremtiden.

Aus der Einleitung: "Auf der Hannovermesse 2011 wurde zum ersten Mal der Begriff "Industrie 4.0" der Öffentlichkeit bekannt gemacht. Die Akademie der Technikwissenschaften hat in einer Arbeitsgruppe diese Grundidee der vierten Revolution der Industrieproduktion weiterbearbeitet und 2013 in einem Abschlussbericht mit dem Titel „Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0“ veröffentlicht (BmBF, 2013). Die Grundidee besteht darin, wandlungsfähige und effiziente Fabriken unter Nutzung moderner Informationstechnologie zu entwickeln. Basistechnologien für die Umsetzung der intelligenten Fabriken sind: — Cyber-Physical Systems (CPS) — Internet of Things (IoT) und Internet of Services (IoS) — Big Data Analytics and Prediction — Social Media — Mobile Computing Der Abschlussbericht fokussiert den Wertschöpfungsschritt der Produktion, während die Fragen der Produktentwicklung weitgehend unberücksichtigt geblieben sind. Die intelligente Fabrik zur Herstellung intelligenter Produkte setzt aber auch die Weiterentwicklung der Produktentwicklungsmethoden voraus. Auch hier gibt es einen großen Handlungsbedarf, der sehr stark mit den Methoden des „Modellbasierten Systems-Engineering“ einhergeht. ..."

Industry 4.0 is changing the manufacturing environment with its cyber-physical infrastructure to support and help increase production performance. The cyber-physical infrastructure brings new technologies such as Internet of Things, big data, cloud computing, and machine learning using advanced algorithms. To deal with this new order to preserve asset performance, industrial maintenance needs to be prepared. This study aims to understand the impact of Industry 4.0 on the skills required within industrial maintenance departments. A survey of industrial maintenance professionals finds that the majority of training comes from internal sources and that much of the information systems used for training are out-of-date or does not exist. The results of this study show that Industry 4.0 will impact the maintenance department and that a Change Management process should be put in place to accomplish this transition smoothly.

Recent developments in the area of Cyber-Physical Production Systems prove that high technology readiness level is already achieved and industrialization of such technologies is not far from today. Although these technologies seem to be convenient in providing solutions to environmental uncertainties, their application provides adaptability only at shop floor level. Needless to say, an enterprise cannot reach true adaptability without ensuring adaptation skills at every level in its hierarchy. Commonly used production planning and control approaches in industry today inherit from planning solutions which are developed in response to historical market characteristics. However, market tendency in recent years is towards making personalized products a norm. The emerging complexity out of this trend obliges planning systems to a transition from non-recurring, static planning into continuous re-planning and re-configuration of systems. Therefore, there is a need of responsive planning solutions which are integrated to highly adaptable production system characteristics. In this dissertation, Demand Responsive Planning, DRP, is presented which is a planning framework aiming to respond to planning needs of shifting trends in both production system technologies and market conditions. The DRP is based on three main constructs such as dynamicity, responsiveness and use of precise data. These features set up the foundation of accomplishing a high degree of adaptability in planning activities. By this means, problems from an extensive scope can be handled with a responsive behavior (i.e. frequent re-planning) by the use of precise data. The use of precise data implies to execute planning activities subject to actual demand information and real-time shop floor data. Within the context of the DRP, both a continuous workload control method and a dynamic capacity adjustment approach are developed. A test-bed is coded in order to simulate proposed method based on a system emulation reflecting the characteristics of cyber-physical production systems at shop floor level. Continuous Precise Workload Control, CPWLC, method is a novel approach aiming at precise control of workload levels with the use of direct load graphs. Supported by a multi-agent platform, it generates dynamic non-periodic release decisions exploiting real time shop floor information. As a result, improved shop floor performances are achieved through controlling workload levels precisely by the release of appropriate job types at the right time. Presented dynamic capacity adjustment approach utilizes rapid re-configuration capability of cyber-physical systems in achieving more frequent capacity adjustments. Its implementation architecture is integrated to the CPWLC structure. By this means, a holistic approach is realized whereby improved due date performance is accomplished with minimized shop floor congestion. Hence, sensitivity to changing demand patterns and urgent job completions is improved. / <p>QC 20150907</p>

Industry 4.0 is one of the fastest growing topics amongst both practitioners and academics. To this day, no definition of Industry 4.0 has reached consensus. However, some definitions can be considered more correct than others and the most accurate one is summarized as “Industry 4.0 is a concept for creating value throughout the whole value-chain”. This has been made possible through digital solutions, advanced technologies, which often are associated with Industry 4.0. This thesis started off finding the key aspects of Industry 4.0 and through a literature review it was concluded to be Cyber-Physical Systems (CPS) which will bring new innovative Business Models. The fundamental aspect of Industry 4.0 is data, data which has become available through the usage of CPS, data which will transform how business are conducted. This thesis aims to develop a better understanding for how CPS affects the Business Model. The thesis started with a literature review, investigating the value of information in a digitalized era. It was established that the value is found in the capability to monitor, remote control, optimize, and automate products and machines. Furthermore, it was also established through the literature review that manufacturing industries are becoming more services-focused and that value-creation is done through networking. Moreover, the Business Model Canvas was embraced as theoretical framework for what a business model should consist of. Data was gathered through semi-structured interviews with experts on the subject of Industry 4.0 and digitalization. The data was then compared to the theoretical framework. The results showed that CPS will not affect business models in any direct way as it is very well founded that the business model always should be based on the customer segment. However, CPS did have an indirect impact on business models i.e. through expected changes in customer relationships and distribution channels, but foremost, through changes regarding specialization and partnerships.

Το αντικείμενο της παρούσας διπλωματικής εργασίας αφορά την ανάλυση και τον έλεγχο κυβερνοφυσικών δικτυωμένων δυναμικών συστημάτων. Ειδικότερα, μελετώνται γραμμικά χρονικά αμετάβλητα συστήματα μίας εισόδου με περιορισμούς τόσο στην είσοδο όσο και στο διάνυσμα καταστατικών μεταβλητών και προτείνονται στρατηγικές ανταγωνιστικού ελέγχου. Συγκεκριμένα, ένας βέλτιστος ελεγκτής εξασφαλίζει θετική αμεταβλητότητα ενός φραγμένου κυρτού πολυεδρικού συνόλου ως προς το σύστημα και ταυτόχρονα σύγκλιση της τροχιάς του διανύσματος κατάστασης στο μηδέν το συντομότερο δυνατό. Υποθέτουμε ότι ένας «ανταγωνιστής » ελεγκτής επιτυγχάνει κατά διαστήματα να αναλάβει τον έλεγχο του συστήματος και αποστέλλει μέσω του δικτύου εσφαλμένα σήματα εισόδου στοχεύοντας να οδηγήσει το διάνυσμα κατάστασης εκτός του πολυεδρικού συνόλου το συντομότερο δυνατό. Προσομοιώσεις καταδεικνύουν ότι το διακοπτικό φαινόμενο που ανακύπτει από τη διαδοχική εφαρμογή των δύο παραπάνω ελεγκτών προκαλεί μία περιοδική τροχιά του διανύσματος κατάστασης. Τα θεωρητικά εργαλεία που χρησιμοποιήθηκαν για την εξαγωγή των αποτελεσμάτων προέρχονται από τη θεωρία ευστάθειας Lyapunov και τη θεωρία αμετάβλητων συνόλων. / This thesis addresses the analysis and control of networked cyber-physical dynamical systems. We are mostly concerned with the study of linear, time-invariant systems with single input. The systems evolve in the discrete time and are subject to both state and input constraints and a certain number of adversary control strategies are proposed. A time-optimal control law guarantees positive invariance of a bounded convex polyhedral set with respect to the given system, while contracting the state space vector to the origin. At times, an adversary controller succeeds in gaining control of the system and sends false control commands attempting to lead the state vector outside the polyhedral set at the maximum admissible rate. Simulation studies highlight that consecutively applying the above control laws results in a periodic motion of the state vector. The theoretic tools used to obtain our conclusions associate with Lyapunov stability and set theory.

Cyber-Physical Systems theory is a new concept that is about to revolutionize the way computers interact with the physical world by integrating physical knowledge into the computing systems and tailoring such computing systems in a way that is more compatible with the way processes happen in the physical world. In this master’s thesis, Field Programmable Gate Arrays (FPGA) are studied as a potential technological asset that may contribute to the enablement of the Cyber-Physical paradigm. As an example application that may benefit from cyber-physical system support, the Electro-Slag Remelting process - a process for remelting metals into better alloys - has been chosen due to the maturity of its related physical models and controller designs. In particular, the Particle Filter that estimates the state of the process is studied as a candidate for FPGA-based computing enhancements. In comparison with CPUs, through the designs and experiments carried in relationship with this study, the FPGA reveals itself as a serious contender in the arsenal of v computing means for Cyber-Physical Systems, due to its capacity to mimic the ubiquitous parallelism of physical processes. / text

Designing Cyber-Physical Systems is hard. Physical testing can be slow, expensive and dangerous. Furthermore computational components make testing all possible behavior unfeasible. Model-based design mitigates these issues by making it possible to iterate over a design much faster. Traditional simulation tools can produce useful results, but their results are traditionally approximations that make it impossible to distinguish a useful simulation from one dominated by numerical error. Verification tools require skills in formal specification and a priori understanding of the particular dynamical system being studied. This thesis presents rigorous simulation, an approach to simulation that uses validated numerics to produce results that quantify and bound all approximation errors accumulated during simulation. This makes it possible for the user to objectively and reliably distinguish accurate simulations from ones that do not provide enough information to be useful. Explicitly quantifying the error in the output has the side-effect of leading to a tool for dealing with inputs that come with quantified uncertainty. We formalize the approach as an operational semantics for a core subset of the domain-specific language Acumen. The operational semantics is extended to a larger subset through a translation. Preliminary results toward proving the soundness of the operational semantics with respect to a denotational semantics are presented. A modeling environment with a rigorous simulator based on the operational semantics is described. The implementation is portable, and its source code is freely available. The accuracy of the simulator on different kinds of systems is explored through a set of benchmark models that exercise different aspects of a rigorous simulator. A case study from the automotive domain is used to evaluate the applicability of the simulator and its modeling language. In the case study, the simulator is used to compute rigorous bounds on the output of a model.

Cyber-physical systems (CPS) integrate sensing, computing, communication and actuation capabilities to monitor and control operations in the physical environment. A key requirement of such systems is the need to provide predictable real-time performance: the timing correctness of the system should be analyzable at design time with a quantitative metric and guaranteed at runtime with high assurance. This requirement of predictability is particularly important for safety-critical domains such as automobiles, aerospace, defense, manufacturing and medical devices. The work in this dissertation focuses on the challenges arising from the use of modern multi-core platforms in CPS. Even as of today, multi-core platforms are rarely used in safety-critical applications primarily due to the temporal interference caused by contention on various resources shared among processor cores, such as caches, memory buses, and I/O devices. Such interference is hard to predict and can significantly increase task execution time, e.g., up to 12 commodity quad-core platforms. To address the problem of ensuring timing predictability on multi-core platforms, we develop novel analytical and systems techniques in this dissertation. Our proposed techniques theoretically bound temporal interference that tasks may suffer from when accessing shared resources. Our techniques also involve software primitives and algorithms for real-time operating systems and hypervisors, which significantly reduce the degree of the temporal interference. Specifically, we tackle the issues of cache and memory contention, locking and synchronization, interrupt handling, and access control for computational accelerators such as general-purpose graphics processing units (GPGPUs), all of which are crucial to achieving predictable real-time performance on a modern multi-core platform. Our solutions are readily applicable to commodity multi-core platforms, and can be used not only for developing new systems but also migrating existing applications from single-core to multi-core platforms.