CPS: Breakthrough: Scalable Component-Based Model Revision of Cyber-Physical Systems with Separation of Concerns
Lead PI:
Sandeep Kulkarni
Abstract
This project develops algorithms for revising a given model for a cyber-physical system while ensuring that the revised model is correct-by-construction and is realizable in the constraints imposed by the cyber-physical system. It specializes these algorithms in the context of fault-tolerance (with the theory of separation of concerns) and in the context of timed models (with the role of fairness). The project identifies constraints imposed by the inability to revise some or all physical components and ensure that they are satisfied during revision. It specializes model revision algorithms in two contexts: fault-tolerance and role of fairness during revision. Regarding fault-tolerance, it develops the theory of separation of concerns for cyber-physical systems. This work bridges the gap between fault-tolerance components, control theory and model revision. Regarding fairness, it develops efficient algorithms for revision by using abstraction to model continuous behaviors with discrete behaviors that utilize fairness. One broad impact of this project is to advance the fundamental science and technology of cyber-physical systems by developing systematic methods that ensure system correctness during maintenance where the system is revised due to changing requirements and/or environment. The algorithms from this project will provide techniques for providing assurance in automotive and aeronautical systems. In the context where fault-tolerance properties are added, the proposed activities also have the potential to identify missing specifications early and thereby reduce the cost of designing corresponding systems. The proposed activities facilitate in educating graduate students about different tasks involved in providing assurance via component based models and via model revision.
Sandeep Kulkarni
Performance Period: 10/01/2013 - 09/30/2016
Institution: Michigan State University
Sponsor: National Science Foundation
Award Number: 1329807