ATD: Collaborative Research: Estimation of Nonlinear Components and Disturbances in Dynamical Systems with Applications to Threat Detection

University Of Maryland Baltimore County, Baltimore MD

Investigators

Abstract

This project aims to develop efficient statistical algorithms for estimation of complex dynamics, nonlinear components and disturbances, with applications to threat detection in engineering and biological systems. Four interconnected research tasks will be addressed: (1) partial state estimation of dynamical systems; (2) adaptive smoothing spline estimation of functions with varying roughness; (3) P-spline estimation of shape restricted functions; and (4) estimation and threat detection of power systems, genetic networks, and engineering systems. By integrating novel techniques from asymptotic statistics, optimization and control theory, theoretically sound and efficient detection algorithms will be developed and be applied to potentially transformative systems. A number of critical national infrastructure and important engineering or biological systems consist of numerous components and are constantly subject to disturbances. The failure of these components and/or hazardous disturbances pose threats to national security, economy and health. The success of this project will allow practitioners to better predict system dynamics and imminent threats, and therefore to avoid potentially damaging consequences. In particular, it will be useful for detecting adverse disturbances in power systems, deepen the understanding of dynamical behaviors of epidemiological diseases, and improve precision and reliability of aerospace and other engineering systems. The investigators will also actively pursue various educational and outreach activities by engaging students at all levels to strengthen and broaden awareness of science, technology, engineering, and mathematics.