SGER: Modeling, Analysis, and Diagnosis for Safety of Distributed Hybrid Systems

Vanderbilt University, Nashville TN

Investigators

Abstract

CNS-0452067 Gautam Biswas Title: SGER: Modeling, Analysis, and Diagnosis for Safety of Distributed Hybrid Systems Distributed embedded systems are pervading all aspects of our daily lives, from home appliances to safety and mission critical systems, such as automobiles, aircraft, manufacturing processes, nuclear plants, and military systems. These engineered systems consist of multiple subsystems with software components tightly integrated into physical processes. Complete analysis of their behaviors at design time is computationally infeasible. Diagnosis of fault behavior and its potential propagation through highly-coupled complex systems lacks a comprehensive scientific foundation. Commonly used methods for fault and failure mode criticality analysis do not address the detailed interactions of these systems and do not scale. A key observation is that the coupled subsystems interact at the physical level through energy-related interactions and at the logical level, by information exchange typically facilitated by a communication fabric such as a local area network LAN or control network. The objectives and primary thrust areas of this exploratory research effort are two-fold. (i) Advance the scientific understanding of modeling and behavior analysis of complex, embedded systems that are made up of distributed, interacting subsystems. This will require developing modeling methodologies and languages that integrate heterogeneous paradigms, developing formal models and mechanisms to handle subsystem interactions, and parameterizing the models to facilitate fault analysis. (ii) Develop practical technologies for safety analysis and online diagnosis of complex distributed systems. The significant challenge in building a systematic framework for distributed diagnosis is to specify the coupling between subsystems in a way that fault interactions are captured in sufficient detail and integrated into the hybrid modeling methodology. It is also important to combine the results of the subsystem diagnostic components in a computationally efficient manner. The science and technology developed in this project will inform designers in how to build more effective, reliable, and verifiable systems. For rapid dissemination through graduating engineers, research results will also be introduced in undergraduate and graduate engineering classes and laboratories at Vanderbilt University. Besides regular publications, efforts will be made to run a focused workshop in this area.