This is the wiki for the NSF CPS project CPS: Small: Energy-Aware Formal Synthesis for Supervisory Control and Information Acquisition in Cyber-Physical Systems
NSF award number: CNS-1738103. Project period: 10/01/2017 - 09/30/2021
This project is developing theoretical foundations and computational algorithms for synthesizing higher-level supervisory and information-acquisition control logic in cyber-physical systems that expend or replenish their resources while interacting with the environment. On the one hand, qualitative requirements capture the safety requirements that are imposed on the system as it operates. On the other hand, quantitative requirements capture resource constraints in the context of energy-aware systems. These dual considerations are needed in applications of cyber-physical systems where efficient management of resources must be accounted for in the dynamic operation of the system in order to achieve the desired objectives within a given energy or resource budget.
The approach pursued is formal and model-based. It leverages a recently-developed unified framework for supervisory control and information acquisition in the higher-level control logic of cyber-physical systems, but it explicitly embeds quantitative constraints in the solution procedure in order to capture the energy or resources expended and/or replenished by the cyber-physical system as it interacts with its environment. This generic solution methodology is applicable to several classes of cyber-physical systems subject to energy constraints. Software tools are being developed to facilitate the transition of these results to application domains. Of special interest is energy-aware mission planning in autonomous systems, a rich domain where qualitative mission requirements are coupled with quantitative constraints. Overall, this project impacts both the Science of Cyber-Physical Systems and the Engineering of Cyber-Physical Systems.
The software tools developed in this project are being integrated within the suite of tools contained in the GitLab repository M-DES-tools of the UMDES group at the University of Michigan. Please refer to that site.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.