Task-driven Modular Co-design of Vehicle Control Systems

When designing autonomous systems, we need to consider multiple trade-offs at various abstraction levels, and the choices of single (hardware and software) components need to be studied jointly. In this work we consider the problem of designing the control algorithm as well as the platform on which it is executed. In particular, we focus on vehicle control systems, and formalize state-of-the-art control schemes as monotone feasibility relations. We then show how, leveraging a monotone theory of co-design, we can study the embedding of control synthesis problems into the task-driven co-design problem of a robotic platform. The properties of the proposed approach are illustrated by considering urban driving scenarios. We show how, given a particular task, we can efficiently compute Pareto optimal design solutions.Comment: 8 pages, 7 figures. Proceedings of the 2022 IEEE 61th Conference on Decision and Contro

Co-Design of Autonomous Systems: From Hardware Selection to Control Synthesis

Designing cyber-physical systems is a complex task which requires insights at multiple abstraction levels. The choices of single components are deeply interconnected and need to be jointly studied. In this work, we consider the problem of co-designing the control algorithm as well as the platform around it. In particular, we leverage a monotone theory of co-design to formalize variations of the LQG control problem as monotone feasibility relations. We then show how this enables the embedding of control co-design problems in the higher level co-design problem of a robotic platform. We illustrate the properties of our formalization by analyzing the co-design of an autonomous drone performing search-and-rescue tasks and show how, given a set of desired robot behaviors, we can compute Pareto efficient design solutions.Comment: 8 pages, 6 figures, to appear in the proceedings of the 20th European Control Conference (ECC21

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

CONTREX: Design of embedded mixed-criticality CONTRol systems under consideration of EXtra-functional properties

The increasing processing power of today’s HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels. This article presents an overview of the CONTREX European project, its main innovative technology (extension of a model based design approach, functional and extra-functional analysis with executable models and run-time management) and the final results of three industrial use-cases from different domain (avionics, automotive and telecommunication).The work leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2011 under grant agreement no. 611146

Digital Twins and Blockchain for IoT Management

Security and privacy are primary concerns in IoT management. Security breaches in IoT resources, such as smart sensors, can leak sensitive data and compromise the privacy of individuals. Effective IoT management requires a comprehensive approach to prioritize access security and data privacy protection. Digital twins create virtual representations of IoT resources. Blockchain adds decentralization, transparency, and reliability to IoT systems. This research integrates digital twins and blockchain to manage access to IoT data streaming. Digital twins are used to encapsulate data access and view configurations. Access is enabled on digital twins, not on IoT resources directly. Trust structures programmed as smart contracts are the ones that manage access to digital twins. Consequently, IoT resources are not exposed to third parties, and access security breaches can be prevented. Blockchain has been used to validate digital twins and store their configuration. The research presented in this paper enables multitenant access and customization of data streaming views and abstracts the complexity of data access management. This approach provides access and configuration security and data privacy protection.Comment: Reference: Mayra, Samaniego and Ralph, Deters. 2023. Digital Twins and Blockchain for IoT Management. In The 5th ACM International Symposium on Blockchain and Secure Critical Infrastructure (BSCI '23), July 10-14, 2023, Melbourne, VIC, Australia. ACM, New York, NY, USA, 11 pages. https://doi.org/10.1145/3594556.359461

Co-design of Control and Scheduling in Networked Systems under Denial-of-Service attacks

We consider the joint design of control and scheduling under stochastic Denial-of-Service (DoS) attacks in the context of networked control systems. A sensor takes measurements of the system output and forwards its dynamic state estimates to a remote controller over a packet-dropping link. The controller determines the optimal control law for the process using the estimates it receives. An attacker aims at degrading the control performance by increasing the packet-dropout rate with a DoS attack towards the sensor-controller channel. Assume both the controller and the attacker are rational in a game-theoretic sense. We establish a partially observable stochastic game to derive the optimal joint design of scheduling and control. Using dynamic programming we prove that the control and scheduling policies can be designed separately without sacrificing optimality, making the problem equivalent to a complete information game. We employ Nash Q-learning to solve the problem and prove that the solution is guaranteed to constitute an $\epsilon$-Nash equilibrium. Numerical examples are provided to illustrate the tradeoffs between control performance and communication cost.Comment: 9 pages, 4 figure