Power systems are being operated closer to their stability limits due to the continuing trends of increasing power demand and lack of expansion in transmission capacity. There is a mismatch in highly stressed power systems between the stability characteristics predicted by advanced modeling and simulation and the actual stability of the real system. This mismatch results in overly optimistic stability assessment, with sometimes catastrophic consequences. The goal of this SGER proposal is to begin the development of a non-model-based approach to detecting closeness to instability of uncertain power systems in real time. Intellectual Merit: Signal-based techniques will be sought for real-time detection and monitoring of closeness to instability for electric power networks in stressed conditions. An important tool in this work is the concept of precursors for instability, signatures of measured system outputs that appear when a system approaches its stability limits. The methods will be applied to electric power system models which will be used to mimic real conditions of stability margin assessment with uncertain models in stressed conditions. Broader Impact: Success in this effort can be of critical importance not only in power system blackout avoidance, but also in earthquake warning systems, medical device design (such as for management of heart attacks and brain seizures), and development of government economic policy for avoidance of catastrophic events in the economy or in financial markets. Mathematical modeling alone is incapable of accurately predicting the onset of instability in any of these applications.