Les systèmes de contrôle-commande industriels (Industrial Control System, ICS) sont des infrastructures constituées par un ensemble de calculateurs industriels reliés en réseau et permettant de contrôler un système physique. Ils assurent le pilotage de réseaux électriques (Smart Grid), de systèmes de production, de transports, de santé ou encore de systèmes d’armes. Pensés avant tout pour assurer productivité et respect de la mission dans un environnement non malveillant, les ICS sont, depuis le 21ème siècle, de plus en plus vulnérables aux attaques (Stuxnet, Industroyer, Triton, …) notamment avec l’arrivée de l’industrie 4.0. De nombreuses études ont contribué à sécuriser les ICS avec des approches issues du domaine de la sécurité (cryptographie, IDS, etc…) mais qui ne tiennent pas compte du comportement du système physique et donc des conséquences de l’acte de malveillance en lui-même. Ainsi, une sécurisation se limitant exclusivement à l’analyse des informations qui transitent sur un réseau industriel n’est pas suffisante. Notre approche amène un changement de paradigme dans les mécanismes de détection en y intégrant la modélisation du comportement du système cyber-physique.Cette thèse propose des mécanismes de détection d’attaques en se positionnant au plus proche de la physique. Ils analysent les données échangées entre le système de contrôle-commande et le système physique, et filtrent les échanges au travers de modèles déterministes qui représentent le comportement du système physique soumis à des lois de commande. A cet effet, une méthodologie de conception a été proposée dans laquelle l’ensemble des ordres est identifié afin de détecter les attaques brutales. Pour faire face aux autres attaques, en particulier celles plus sournoises, comme les attaques par séquences, nous proposons une stratégie de détection complémentaire permettant d’estimer l’occurrence d’une attaque avant que ses conséquences ne soient destructives. A cet effet, nous avons développé des concepts de distance d’un état caractérisé comme critique auquel nous avons adjoint un second mécanisme dit de trajectoire dans le temps permettant de caractériser une intention de nuire.L’approche proposée hybride ainsi deux techniques orientées sécurité (sonde IDS) et sûreté (approche filtre) pour proposer une stratégie de détection basée sur quatre mécanismes lié :• A la détection de contexte : basé sur l’état courant de l’ICS, un ordre émis par l’API peut être bloqué s’il conduit vers un état critique (attaque brutale).• Aux contraintes combinatoires (attaque par séquences) : vérifiées par les concepts de distance et de trajectoire (évolution de la distance).• Aux contraintes temporelles (attaque temporelle) : vérifiées par des fenêtres temporelles sur l’apparition d’évènements et d’indicateurs surveillant la durée moyenne d’exécution.• Aux sur-sollicitations basées sur un indicateur surveillant les commandes envoyées afin de prévenir un vieillissement prématuré (attaque sur les équipements).L’approche proposée a été appliquée sur différents exemples de simulation et sur une plateforme industrielle réelle où la stratégie de détection a montré son efficacité face à différents profils d’attaquant. / Industrial Control Systems (ICSs) are infrastructures composed by several industrial devices connected to a network and used to control a physical system. They control electrical power grid (Smart Grid), production systems (e.g. chemical and manufacturing industries), transport (e.g. trains, aircrafts and autonomous vehicles), health and weapon systems. Designed to ensure productivity and respect safety in a non-malicious environment, the ICSs are, since the 21st century, increasingly vulnerable to attacks (e.g. Stuxnet, Industroyer, Triton) especially with the emergence of the industry 4.0. Several studies contributed to secure the ICS with approaches from the security field (e.g. cryptography, IDS) which do not take into account the behavior of the physical system and therefore the consequences of the malicious act. Thus, a security approach limited exclusively to the analysis of information exchanged by industrial network is not sufficient. Our approach creates a paradigm shift in detection mechanisms by integrating the behavioral modeling of the cyber-physical system.This thesis proposes detection mechanisms of attacks by locating detection closer to physical system. They analyze the data exchanged between the control system and the physical system, and filter the exchanges through deterministic models that represent the behavior of the physical system controlled by control laws. For this purpose, a design methodology has been proposed in which all actions are identified in order to instantly detect brutal attacks. To deal with other attacks, especially the more sneaky, such as sequential attacks, we propose a complementary detection strategy to estimate the occurrence of an attack before its consequences are destructive. To this end, we have developed the concepts of distance of a state identified as critical to which we have added a second mechanism called trajectory which leads to a temporal notion that characterize an intention to harm.As part of this thesis, the proposed approach combines two techniques oriented security (IDS probe) and safety (filter approach) to propose a detection strategy based on four mechanisms related to:• Context detection: based on the current state of the system, an order sent by the PLC can be blocked by the control filter if it leads to a critical state (brutal attack).• Combinatorial constraints (sequential attack): verified by the concepts of distance (risk indicator for the current state) and trajectory (indicator of the intention to harm by studying the evolution of the distance on a sequence).• Temporal constraints (temporal attack): verified by time windows on the appearance of events and an indicator monitoring the average duration of execution.• Over-solicitation monitoring mechanism: based on an indicator monitoring orders sent to the actuators to prevent premature ageing of the production equipment (attack on the equipment).The proposed approach has been applied to various simulation examples and an industrial platform where the detection strategy has shown its effectiveness against different scenarios corresponding to attacker profiles.

This research proposes Stress-Lysis, iLog and SaYoPillow to automatically detect and monitor the stress levels of a person. To self manage psychological stress in the framework of smart healthcare, a deep learning based novel system (Stress-Lysis) is proposed in this dissertation. The learning system is trained such that it monitors stress levels in a person through human body temperature, rate of motion and sweat during physical activity. The proposed deep learning system has been trained with a total of 26,000 samples per dataset and demonstrates accuracy as high as 99.7%. The collected data are transmitted and stored in the cloud, which can help in real time monitoring of a person's stress levels, thereby reducing the risk of death and expensive treatments. The proposed system has the ability to produce results with an overall accuracy of 98.3% to 99.7%, is simple to implement and its cost is moderate. Chronic stress, uncontrolled or unmonitored food consumption, and obesity are intricately connected, even involving certain neurological adaptations. In iLog we propose a system which can not only monitor but also create awareness for the user of how much food is too much. iLog provides information on the emotional state of a person along with the classification of eating behaviors to Normal-Eating or Stress-Eating. This research proposes a deep learning model for edge computing platforms which can automatically detect, classify and quantify the objects in the plate of the user. Three different paradigms where the idea of iLog can be performed are explored in this research. Two different edge platforms have been implemented in iLog. The platforms include mobile, as it is widely used, and a single board computer which can easily be a part of network for executing experiments, with iLog Glasses being the main wearable. The iLog model has produced an overall accuracy of 98% with an average precision of 85.8%. Smart-Yoga Pillow (SaYoPillow) is envisioned as a device that may help in recognizing the importance of a good quality sleep to alleviate stress while establishing a measurable relationship between stress and sleeping habits. A system that analyzes the sleeping habits by continuously monitoring the physiological changes that occur during rapid eye movement (REM) and non-rapid eye movement (NREM) stages of sleep is proposed in the current work. In addition to the physiological parameter changes, factors such as sleep duration, snoring range, eye movement, and limb movements are also monitored. The SaYoPillow system is processed at the edge level with the storage being at the cloud. SaYoPillow has 96% accuracy which is close to other existing research works. This research can not only help in keeping an individual self-aware by providing immediate feedback to change the lifestyle of the person in order to lead a healthier life, but can also play a significant role in the state-of-the-art by allowing computing on the edge devices.

The Master’s thesis deals with design of digital twins of machine tools and application of designed procedure on a case study – digital twin of the machine tool MCV 754 Quick. In the first part are described current roles of digital twins in the field of machine tools and also hardware and software options for creating them. Software and hardware tools by Siemens (Mechatronics Concept Designer and SIMIT) are used for the case study. The complex procedure of creating the digital twin is designed in the second part, starting with preparation of a model, ending with the virtual commissioning of the machine tool MCV 754 Quick. The procedure is described in detail, including preparation of 3D model of the machine tool, assignment of physical properties and joints, preparation of PLC, connection all the elements of the whole system: Sinumerik – SIMIT – Mechatronics Concept Designer and controlling the twin via CNC automation system. Output of the thesis is the virtually commissioned machine tool, capable of being controlled by Sinumerik 840D sl. This is the first step in development of the full-fledged digital twin of machine tool, which can be used for testing the functionality and capability of this new technology in industry.

Cyber-physikalische Systeme (CPS) sind eine erweitere Sicht auf eingebettete Systeme, die die konkreten umgebenden Elemente in das Systemdesign einbeziehen. Das Design solcher Systeme erfordert neue Herangehensweisen: Während beispielsweise in "normalen" verteilten Systemen Aspekte wie "Bewegung" oder "Ort" möglichst transparent und damit für den Nutzer unsichtbar gestaltet werden, benötigen CPS-Anwendungen häufig Bewusstsein für Bewegung oder Ort, d.h., sie sind _motion aware_ oder _location aware_. Die Professur "Betriebssysteme" der TUC hat sich die Frage gestellt, wie eine generische Unterstützung für solche verteilte mobile Systeme aussehen könnte. Im Vortrag werden Probleme, Konzepte und erste Lösungsansätze für ein künftiges Betriebssystem für diese Art von Systemen vorgestellt.

Technological advances (e.g., high speed communication, artificial intelligence) and affordable computing and sensor hardware have become a key driver of developments like “Industry 4.0” or the “Industrial Internet of Things” (IIoT). Large numbers of machines and products are equipped with sensors to constantly monitor their condition, log usage data or trigger control processes. IIoT has been largely adopted by OEMs in various industries (such as automotive, machinery industry, or healthcare and medical), turning their product into cyber-physical systems. However, the resulting potential is not yet accessible to component manufacturers. Overall, horizontal integration of the value chain is still in its infancy. Specifically, IIoT for fluid powers just started in recent years with first research projects and commercial solutions. This work presents a reference architecture for cyber-physical fluid power systems which depicts how horizontal integration can be achieved and which potentials thus can be released. The architecture is validated in an industrial use case. Furthermore, the paper at hand discusses which components of the architecture should be addressed by which actor in the fluid power ecosystem in order to leverage opportunities from the IIoT.

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This thesis aims to develop and evaluate a dashboard design that visualizes a stream of data from the different entities involved in autonomous warehouses, a subset of cyber-physical systems. I created this dashboard through User-Centered Design (UCD) methodologies based on two feedback iterations with the stakeholders employing semi-structured expert opinion interviews. This thesis also discusses the different stages involved in building this dashboard design, the design decisions, the technical aspects of the libraries used, and the feedback session towards the end of the project. It also presents the implemented dashboard as a proof of development efforts and explains its different functionalities. The project concludes with evaluating the dashboard through a semi-structured interview with the respective stakeholders and suggests features for further development. / Denna studie ämnar att utveckla och utvärdera en design för ett dashboard som visualiserar dataströmmar från olika enheter som kan hittas i autonoma lager. Detta dashboard har utvecklats genom att använda metoder inom användarcentrerad design, som baserades på två iterationer med intressenter som är experter inom området, där semistrukturerade intervjuer gjordes. Denna studie diskuterar också de olika steg som är involverade i att bygga designen av detta dashboard, de olika beslut som togs i designprocessen, de tekniska aspekterna av de bibliotek som används och resultatet från de sessioner som hölls för att få feedback i slutet av projektet. Studien presenterar också det dashboard som utvecklades samt förklarar dess funktionalitet. Slutsatser dras från de semistrukturerade intervjuerna med respektive intressent och föreslår framtida funktioner som skulle vara möjliga att implementera.

Autonomous Driving Systems (ADS), a subcategory of Cyber-Physical Systems (CPS) are becoming increasingly popular with ubiquitous deployment. They provide advanced operational functions for perception and control, but this also raises the question of their safety capability. Such questions include if the vehicle can stay within its lane, keep a safe distance from the leading vehicle, or avoid obstacles, especially under the presence of uncertainties. In this master thesis, the operational safety of ADS will be addressed, more specifically on the Adaptive Cruise Control (ACC) system by modeling an optimal control problem based on Control Barrier Function (CBF) unified with Model Predictive Control (MPC). The corresponding optimal control problem is robust against measurement uncertainties for an Autonomous Vehicle (AV) driving on a highway, where the measurement uncertainties will represent the common faults in the perception system of the AV. A Kalman Filter (KF) is also added to the system to investigate the performance difference. The resulting framework is implemented and evaluated on a simulation scenario created in the open-source autonomous driving simulator CARLA. Simulations show that MPC-CBF is indeed robust against measurement uncertainties for well-selected horizon and slack variable values. The simulations also show that adding a KF improves the overall performance. The higher the horizon, the more confident the system becomes as the distance to the leading vehicle decreases. However, this may cause infeasibility where there are no solutions to the optimal control problem during sudden braking as the AV cannot brake fast enough before it crashes. Meanwhile, the smaller the slack variable, the more restrictive becomes CBF where it impacts more on the control input than desired which could also cause infeasibility. The results of this thesis will help to facilitate safety-critical CPS development to be deployed in real-world applications. / Autonoma körsystem (ADS), som är en del av cyberfysiska system (CPS), har blivit alltmer populär med allestädes närvarande användning. Det bidra med avancerade operativa funktioner för perception och styrning, men samtidig väcker detta också frågan om dess säkerhetsförmåga. Sådana frågor inkluderar om fordonet kan hålla sig inom sitt körfält, om det kan hålla ett säkert avstånd till det ledande fordonet eller om det kan undvika hinder, speciellt under osäkerheter hos systemet. I detta examensarbete kommer driftsäkerheten hos ADS att behandlas, mer specifik på adaptiv farthållare (ACC) genom att modellera ett optimalt kontrollproblem baserat på kontrollbarriärfunktion (CBF) förenat med modellförutsägande styrning (MPC). Motsvarande optimalt kontrollproblem är robust mot mätosäkerheter för ett autonomt fordon som kör på en motorväg, där mätosäkerheterna representerar vanliga fel i AV:s perceptionssystem. Ett Kalmanfilter (KF) läggs också till i systemet för att undersöka skillnaden i prestanda. Det resulterande ramverket implementeras och utvärderas på ett simuleringsscenario som skapats i den öppna källkodssimulatorn för autonom körning CARLA. Simulationer visar att MPC-CBF är robust mot mätosäkerheter för väl valda värden för horisont och slackvariabler. Det visar också att systemets prestanda förbättrats ännu mer om ett KF läggs till. Ju större horisont, desto mer självsäkert blir systemet när avståndet till det ledande fordonet minskar. Detta kan dock leda till att det inte finns några lösningar på det optimala kontrollproblemet vid plötslig inbromsning, eftersom fordonet inte hinner bromsa tillräckligt snabbt innan det kraschar. Ju mindre slackvariabeln är, desto mer restriktiv blir CBF som påverkar styrningen mer än vad som är önskvärt vilket också kan leda till olösbart optimalt kontrollproblem. Resultatet från detta examensarbete bär syftet att gynna utvecklingen av säkerhetkritisk CPS som ska användas i praktiska tillämpningar.

Low-power wireless technology is a part and parcel of our daily life, shaping the way in which we behave, interact, and more generally live. The ubiquity of cheap, tiny, battery-powered devices augmented with sensing, actuation, and wireless communication capabilities has given rise to a ``smart" society, where people, machines, and objects are seamlessly interconnected, among themselves and with the environment. Behind the scenes, low-power wireless protocols are what enables and rules all interactions, organising these embedded devices into wireless networks, and orchestrating their communications. The recent years have witnessed a persistent increase in the pervasiveness and impact of low-power wireless. After having spawned a wide spectrum of powerful applications in the consumer domain, low-power wireless solutions are extending their influence over the industrial context, where their adoption as part of feedback control loops is envisioned to revolutionise the production process, paving the way for the Fourth Industrial Revolution. However, as the scale and relevance of low-power wireless systems continue to grow, so do the challenges posed to the communication substrates, required to satisfy ever more strict requirements in terms of reliability, responsiveness, and energy consumption. Harmonising these conflicting demands is far beyond what is enabled by current network stacks and control architectures; the need to timely bridge this gap has spurred a new wave of interest in low-power wireless networking, and directly motivated our work. In this thesis, we take on this challenge with a main conceptual and technical tool: concurrent transmissions (CTX), a technique that, by enforcing nodes to transmit concurrently, has been shown to unlock unprecedented fast, reliable, and energy efficient multi-hop communications in low-power wireless networks, opening new opportunities for protocol design. We first direct our research endeavour towards industrial applications, focusing on the popular IEEE 802.15.4 narrowband PHY layer, and advance the state of the art along two different directions: interference resilience and aperiodic wireless control. We tackle radio-frequency noise by extensively analysing, for the first time, the dependability of CTX under different types, intensities, and distributions of reproducible interference patterns, and by devising techniques to push it further. Specifically, we concentrate on CRYSTAL, a recently proposed communication protocol that relies on CTX to rapidly and dependably collect aperiodic traffic. By integrating channel hopping and noise detection in the protocol operation, we provide a novel communication stack capable of supporting aperiodic transmissions with near-perfect reliability and a per-mille radio duty cycle despite harsh external interference. These results lay the ground towards the exploitation of CTX for aperiodic wireless control; we explore this research direction by co-designing the Wireless Control Bus (WCB), our second contribution. WCB is a clean-slate CTX-based communication stack tailored to event-triggered control (ETC), an aperiodic control strategy holding the capability to significantly improve the efficiency of wireless control systems, but whose real-world impact has been hampered by the lack of appropriate networking support. Operating in conjunction with ETC, WCB timely and dynamically adapts the network operation to the control demands, unlocking an order-of-magnitude reduction in energy costs w.r.t. traditional periodic approaches while retaining the same control performance, therefore unleashing and concretely demonstrating the true ETC potential for the first time. Nevertheless, low-power wireless communications are rapidly evolving, and new radios striking novel trade-offs are emerging. Among these, in the second part of the thesis we focus on ultra-wideband (UWB). By providing hitherto missing networking primitives for multi-hop dissemination and collection over UWB, we shed light on the communication potentialities opened up by the high data throughput, clock precision, and noise resilience offered by this technology. Specifically, as a third contribution, we demonstrate that CTX not only can be successfully exploited for multi-hop UWB communications but, once embodied in a full-fledged system, provide reliability and energy performance akin to narrowband. Furthermore, the higher data rate and clock resolution of UWB chips unlock up to 80% latency reduction w.r.t. narrowband CTX, along with orders-of-magnitude improvements in network-wide time synchronization. These results showcase how UWB CTX could significantly benefit a multitude of applications, notably including low-power wireless control. With WEAVER, our last contribution, we make an additional step towards this direction, by supporting the key functionality of data collection with an ultra-fast convergecast stack for UWB. Challenging the internal mechanics of CTX, WEAVER interleaves data and acknowledgements flows in a single, self-terminating network-wide flood, enabling the concurrent collection of different packets from multiple senders with unprecedented latency, reliability, and energy efficiency. Overall, this thesis pushes forward the applicability and performance of low-power wireless, by contributing techniques and protocols to enhance the dependability, timeliness, energy efficiency, and interference resilience of this technology. Our research is characterized by a strong experimental slant, where the design of the systems we propose meets the reality of testbed experiments and evaluation. Via our open-source implementations, researchers and practitioners can directly use, extend, and build upon our contributions, fostering future work and research on the topic.

More dynamic markets, shorter product life cycles and comprehensive variant management are challenges that dominate today's market. These maxims apply to the automotive sector, which is currently highly exposed to trade wars, changing mobility patterns and the emergence of new technologies and competitors. To meet these challenges, this thesis presents the creation of a digital twin of an existing production line of electric motors using discrete event simulation. Based on a detailed literature research, a step-by-step establishment of the simulation model of the production line using the software Plant Simulation is presented and argued. Finally, different experiments are carried out with the created model to show how a production line can be examined and optimized by means ofsimulation using different parameters. Within the scope of the different experiments regarding the number of workpiece carriers, number of operators as well as buffer sizes, the line was examined concerning the increase of the output. Furthermore, the simulation model was used to make decisions for future investments in additional XXX machines. Four different scenarios were examined and optimized. By examining the different parameters, optimization potentials of XXX% in the first scenario and up to XXX% in the fourth scenario were achieved. Finally, it was proven that the developed simulation model can be used as a tool for optimizing an existing production line and can generate useful investment information. Beyond that, the development of the simulation model can be employed to investigate further business questions at hand for the specific production line in question. / Mer dynamiska marknader, kortare produktlivscykler och omfattande varianthantering är utmaningar som dominerar dagens marknad. Dessa maximer gäller bilindustrin, som för närvarande är mycket utsatt för handelskrig, förändrade rörlighetsmönster och framväxten av ny teknik och nya konkurrenter. För att möta dessa utmaningar innebär denna avhandling skapandet av en digital tvilling av en befintlig produktionslinje av elmotorer med diskret händelsesimulering. Baserat på en detaljerad litteraturforskning presenteras och argumenteras en steg-för-steg-etablering av simuleringsmodellen för produktionslinjen med hjälp av programvaran Plant Simulation. Slutligen utförs olika experiment med den skapade modellen för att visa hur en produktionslinje kan undersökas och optimeras med hjälp av simulering med hjälp av olika parametrar. Inom ramen för de olika experimenten när det gäller antalet arbetsstyckesbärare, antalet operatörer samt buffertstorlekar undersöktes linjen om ökningen av produktionen. Dessutom användes simuleringsmodellen för att fatta beslut för framtida investeringar i ytterligare hårnålsmaskiner. Fyra olika scenarier undersöktes och optimerades. Genom att undersöka de olika parametrarna uppnåddes optimeringspotentialer på XXX % i det första scenariot och upp till XXX % i det fjärde scenariot. Slutligen bevisades det att den utvecklade simuleringsmodellen kan användas som ett verktyg för att optimera en befintlig produktionslinje och kan generera användbar investeringsinformation. Utöver detta kan utvecklingen av simuleringsmodellen användas för att undersöka ytterligare affärsfrågor till hands för den specifika produktionslinjen i fråga.