Distributed embedded systems that consist of multiple interacting subsystems with tightly integrated software components are pervading all aspects of our daily lives. Online fault detection and isolation (FDI) is the key to the safe and reliable operation of these safety critical systems that include automobiles, aircraft, hospital equipment, manufacturing processes, military systems, and nuclear plants. Contrary to its importance, FDI for the safe operation of large, distributed embedded systems is not a solved problem. As a result, in present day systems, almost all fault management and remedial tasks are left to human operators, who often face information overload and stringent time constraints when operating these systems in mission critical operations. The objective of this project is to develop systematic, scalable, robust, online model-based FDI schemes for distributed embedded systems. The novelty of the research centers on (i) hierarchical abstraction schemes for managing the complexity of the FDI task and enabling the design and development of online model-based FDI algorithms that are provably robust and reliable, (ii) a unified framework for diagnosis of multiple types of faults that occur in the physical and the computational parts of embedded systems as well as faults with different fault profiles (abrupt and incipient faults), and (iii) the development of a tool suite for distributed embedded systems for online FDI. Experimental test-beds are used to demonstrate and verify the effectiveness of the developed methods. The impact of the project lies on providing guarantees for reliable safe operation of complex, distributed safety-critical systems.
