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Automated Synthesis of Stochastic Cyber-Physical Systems: A Robust Approach

Project description

Improving reliability and safety of cyber-physical systems

Cyber-physical systems (CPS) are complex computer systems whose mechanisms are controlled by computer-based algorithms. Developing control software for such systems is currently ad hoc and prone to costly errors, particularly in safety-critical applications. To address this, the EU-funded Auto-CyPheR project proposes a novel robust synthesis approach that automatically computes the control software from high-level requirements. This approach helps tackle CPS complexity by developing new abstraction techniques that are robust to model uncertainties. Despite the high-risk nature of merging methodologies from multiple disciplines such as control theory, computer science and probability theory, the research could help transform CPS design principles. This should enable the design of large-scale, reliable and safe CPS that can operate autonomously in uncertain conditions.

Objective

Cyber-physical systems (CPS) are complex systems with tight interactions between cyber elements and physical components. The cyber elements are control algorithms implemented by computer-based software. Developing the embedded control software for CPS is currently ad hoc and error-prone, which has created costly undesired behaviours, particularly in safety-critical applications. Examples of such undesired behaviours include frequency deviation in power networks causing outages or blackouts (e.g. in Jan 2021 in EU, affecting 200k households), crash of airplanes due to software bugs (Boeing 737 Max, costs 15.9 billion euros) or autonomous cars having software bugs (Toyota recalled 65,000 cars in 2015). Nowadays, most of the costs of CPS design is spent on ensuring that the system meets all the requirements especially when it is working in uncertain conditions. In order to design reliable CPS and to reduce the costs of such a design, I propose a novel robust synthesis approach that computes automatically the control software from high-level requirements. This novel approach creates a paradigm shift in CPS design as it computes control software in a push-button manner and eliminates time-consuming, costly post-validation steps. The approach tackles the CPS complexity by developing new abstraction techniques that are compositional and robust to model uncertainties, which will be integrated in a unified framework for automating the design of the control software. This synthesis paradigm is founded on novel compositional similarity relations with coupled uncertainties and coupled computations on abstract models. My project is high-risk because it requires merging and re-thinking different design methodologies from multiple disciplines including control theory, computer science, and probability theory. It is high-gain since it will transform the design principles of CPS to enable designing large-scale yet reliable and safe CPS working autonomously in uncertain conditions.

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Programme(s)

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Topic(s)

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2022-COG

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Host institution

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 993 756,00
Address
HOFGARTENSTRASSE 8
80539 MUNCHEN
Germany

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Region
Bayern Oberbayern München, Kreisfreie Stadt
Activity type
Research Organisations
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 993 756,00

Beneficiaries (1)

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