CPS: Synergy: Collaborative Research: Methodologies for Engineering with Plug-and-Learn Components: Formal Synthesis and Analysis Across Abstraction Layers

Abstract: Effective engineering of complex devices often depends critically on the ability to encapsulate responsibility for tasks into modular agents and ensure those agents communicate with one another in well-defined and easily observable ways. When such conditions are followed, it becomes possible to detect where problems lie so they can be corrected. It also becomes possible to optimize the agents and their communications to improve performance. Cyber-physical systems (like robots, self-piloting aircraft, etc.) modify themselves to improve performance break those conditions in that some agent modules negotiate their own communications and decide their own actions, sometimes taking advantage of the physics of the world in ways we did not anticipate. This renders difficult application of standard engineering tools to accomplish critical fault diagnosis and design optimization. This project will produce analysis methods address the specific needs of cyber-physical systems that, by their natures, break the rules of convention. We will apply these new methods to the design and analysis of self-improving controllers for flapping-wing micro air vehicles. This work will provide advances in both model-checking related formal design methodologies and in module-based self-adaptive control in computationally resource constrained cyber-physical systems. The formal methods advances will significantly expand our ability to properly design and verify systems that tightly couple computation, sensors, and actuators. The specific test application addressed is significant to a number of nationally important security and defense efforts and will directly impact identified national priorities.