No description available.

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.

The Electrical Power Systems (EPS) are indispensable for a Nuclear Power Plant (NPP). The EPS are essential for plant start-up, normal operation, and emergency conditions. Electrical power systems are necessary not only for power generation, transmission, and distribution but also to supply reliable power for plant operation and control system during safe operation, Design Basis Conditions (DBC) and Design Extension Conditions (DEC). According to IAEA Specific Safety Guide SSG-34, EPS are essentially the support systems of many plant equipment. Electrical system, which supply power to plant systems important to nuclear safety, are essential to the safety of an NPP. In recent years, due to the digitization of Instrumentation and Control (I&C) systems, along with their enhanced accuracy, ease of implementing complex functions and flexibility, have been also exposed to sophisticated cyber threats. Despite physical separation and redundant electrical power supply sources, malicious cyber-attacks performed by insiders or outsiders might disrupt the power flow and result in an interruption in the normal operation of an NPP. Therefore, for the uninterrupted operation of a plant, it is crucial to contemplate cybersecurity in the EPS design and implementation. Considering multiple cyber threats, the main objectives of this research work are finding out security vulnerabilities in electrical power systems, simulating potential cyber-attacks and analyzing the impacts of these attacks on the electrical components to protect the electrical systems against these cyber-attacks. An EPS testbed at a small scale was set up, which included commercial I&C and electrical equipment significant for the cybersecurity analysis. The testbed equipment comprises of electrical protection relay (IEC 60255), controller, operating panel, engineering workstation computer, simulation model, etc. to monitor and control the power supply of one or more electrical equipment responsible for a regular operation in an NPP. Simulated cybersecurity attacks were performed using this testbed and the outcomes were examined in multiple iterations, after adding or changing security controls (cybersecurity countermeasures). Analyzing the cybersecurity and performing cyber-attacks on these systems are very advantageous for a real power plant to prepare and protect the plant equipment before any malicious attack happens. This research work conclusively presents cybersecurity analysis, including basic and sophisticated cyber-attack scenarios to understand and improve the cybersecurity posture of EPS in an NPP. The approach was completed by considering the process engineering systems (e.g. reactor core cooling systems) as attack targets and investigating the EPS specific security Defense-in-Depth (DiD) design together with the Nuclear Safety DiD concepts.:CHAPTER 1 INTRODUCTION 1.1 Motivation 1.2 Technical Background 1.3 Objectives of the Ph.D. Project 1.4 State of the Art in Science and Technology CHAPTER 2 FUNDAMENTALS OF CYBERSECURITY AND ELECTRICAL CONTROL AND PROTECTION CONCEPTS 2.1 Electrical Power System 2.2 Electrical Protection System 2.3 Cyber-Physical System 2.4 Industrial Control System 2.5 Safety I&C and Operational I&C Systems 2.6 Safety Objective Oriented Top-Down Approach 2.7 Cybersecurity Concept 2.8 Threat Identification and Characterization in NPP 2.8.1 Design Basis Threat 2.8.2 Attacker Profile 2.8.1 Reported Real-Life NPP Cyber-Attack Examples 2.9 Security Levels 2.10 Summary CHAPTER 3 CYBER-PHYSICAL PROCESS MODELING 3.1 Introduction 3.2 Single Line Diagrams of Different Operational Modes 3.3 Design 3.4 Block Diagram of Simulink Model 3.5 Implementation of Simulink Blocks 3.5.1 Power Generation 3.5.2 Grid Feed 3.5.3 House Load (Feed Water Pump) 3.6 OPC UA Communication 3.7 Summary CHAPTER 4 CYBER THREAT SCENARIOS FOR EPS 4.1 Introduction 4.2 Cyber-Physical System for EPS 4.3 Cyber Threats and Threat Sources 4.3.1 Cyber Threats 4.3.2 Threat Sources 4.4 Cybersecurity Vulnerabilities 4.4.1 Vulnerabilities in EPS 4.4.2 Vulnerabilities in ICS 4.5 Attacker Modeling 4.6 Basic Cyber Threat Scenarios for EPS 4.6.1 Scenario-1: Physical Access to Electrical Cabinets 4.6.2 Scenario-2: Modification of Digital Protection Devices 4.7 Potential Advanced Cyber Threat Scenarios for EPS 4.7.1 Scenario-1: Alteration of a Set-point of the Protection Relay 4.7.2 Scenario-2: Injection of Malicious Packets 4.7.3 Scenario-3: False Trip Command 4.7.4 Scenario-4: Availability Attack on Protection Relay or SCADA System 4.7.5 Scenario-5: Permanent Damage to Physical Component 4.7.6 Scenario-6: Protocol-wise Attack on Operator Panel 4.8 Threat Scenario for Simulink model 4.9 Summary CHAPTER 5 EPS TESTBED DESCRIPTION 5.1 Introduction 5.2 Basic Industrial Automation Architecture 5.3 Need for Testbeds 5.4 Proposed EPS Testbed 5.4.1 Testbed Architecture 5.4.2 Testbed Implementation 5.5 EPS Physical Testbed Applications 5.5.1 Modeling and Simulation of Power System Faults 5.5.2 Modeling of Cyber-Attacks 5.6 Summary CHAPTER 6 EXPERIMENTAL AND IMPACT ANALYSIS OF CYBER THREAT SCENARIOS 6.1 Outline 6.2 Normal Operation and Control 6.3 Possibilities to Cause Failure in the Primary or Secondary Cooling Systems 6.4 Implementation of Cybersecurity Threat Scenarios 6.4.1 Alteration of a Relay Set-Point during Plant Start-Up Phase 6.4.2 Alteration of a Controller Set-Point during Normal Operation Phase 6.4.3 Availability Attack on Control and Protection System 6.4.4 Severe Damage to a Physical Component due to Overcurrent 6.5 Experimentally Assessed Cyber-attacks 6.6 Summary CHAPTER 7 SUMMARY AND OUTLOOK REFERENCES SCIENTIFIC PUBLICATIONS GLOSSARY

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.

No description available.

<p><em>Imbulgoda Liyangahawatte, Gihan Janith Mendis Ph.D., Purdue University, May</em></p> <p><em>2023. Deep learning for securing critical infrastructure with the emphasis on power</em></p> <p><em>systems and wireless communication. Major Professor: Dr. Jin Kocsis.</em></p> <p><br></p> <p><em>Critical infrastructures, such as power systems and communication</em></p> <p><em>infrastructures, are of paramount importance to the welfare and prosperity of</em></p> <p><em>modern societies. Therefore, critical infrastructures have a high vulnerability to</em></p> <p><em>attacks from adverse parties. Subsequent to the advancement of cyber technologies,</em></p> <p><em>such as information technology, embedded systems, high-speed connectivity, and</em></p> <p><em>real-time data processing, the physical processes of critical infrastructures are often</em></p> <p><em>monitored and controlled through cyber systems. Therefore, modern critical</em></p> <p><em>infrastructures are often viewed as cyber-physical systems (CPSs). Incorporating</em></p> <p><em>cyber elements into physical processes increases efficiency and control. However, it</em></p> <p><em>also increases the vulnerability of the systems to potential cybersecurity threats. In</em></p> <p><em>addition to cyber-level attacks, attacks on the cyber-physical interface, such as the</em></p> <p><em>corruption of sensing data to manipulate physical operations, can exploit</em></p> <p><em>vulnerabilities in CPSs. Research on data-driven security methods for such attacks,</em></p> <p><em>focusing on applications related to electrical power and wireless communication</em></p> <p><em>critical infrastructure CPSs, are presented in this dissertation. As security methods</em></p> <p><em>for electrical power systems, deep learning approaches were proposed to detect</em></p> <p><em>adversarial sensor signals targeting smart grids and more electric aircraft.</em></p> <p><em>Considering the security of wireless communication systems, deep learning solutions</em></p> <p><em>were proposed as an intelligent spectrum sensing approach and as a primary user</em></p> <p><em>emulation (PUE) attacks detection method on the wideband spectrum. The recent</em></p> <p><em>abundance of micro-UASs can enable the use of weaponized micro-UASs to conduct</em></p> <p><em>physical attacks on critical infrastructures. As a solution for this, the radio</em></p> <p><em>frequency (RF) signal-analyzing deep learning method developed for spectrum</em></p> <p><em>sensing was adopted to realize an intelligent radar system for micro-UAS detection.</em></p> <p><em>This intelligent radar can be used to provide protection against micro-UAS-based</em></p> <p><em>physical attacks on critical infrastructures.</em></p>

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.

Stop-and-Go Adaptive Cruise Control (ACC+) is an extension of Adaptive Cruise Control (ACC) that works at low speed as well as normal highway speeds to regulate the speed of the vehicle relative to the vehicle it is following. In this thesis, we design an ACC+ controller for a scale model electric vehicle that ensures the robust performance of the system under various models of uncertainty. We capture the operation of the hybrid system via a state-chart model that performs mode switching between different digital controllers with additional decision logic to guarantee the collision freedom of the system under normal operation. We apply different controller design methods such as Linear Quadratic Regulator (LQR) and H-infinity and perform multiple simulation runs in MATLAB/Simulink to validate the performance of the proposed designs. We compare the practicality of our design with existing formally verified ACC designs from the literature. The comparisons show that the other formally verified designs exhibit unacceptable behaviour in the form of mode thrashing that produces excessive acceleration and deceleration of the vehicle. While simulations provide some assurance of safe operation of the system design, they do not guarantee system safety under all possible cases. To increase confidence in the system, we use Differential Dynamic Logic (dL) to formally state environmental assumptions and prove safety goals, including collision freedom. The verification is done in two stages. First, we identify the invariant required to ensure the safe operation of the system and we formally verify that the invariant preserves the safety property of any system with similar dynamics. This procedure provides a high level abstraction of a class of safe solutions for ACC+ system designs. Second, we show that our ACC+ system design is a refinement of the abstract model. The safety of the closed loop ACC+ system is proven by verifying bounds on the system variables using the KeYmaera verification tool for hybrid systems. The thesis demonstrates how practical ACC+ controller designs optimized for fuel economy, passenger comfort, etc., can be verified by showing that they are a refinement of the abstract high level design. / Thesis / Master of Applied Science (MASc)