Publications

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Infrastructure resilience is a priority for homeland security in many nations around the globe. This paper describes a new approach forquantitatively assessing the resilience of critical infrastructure systems. The mathematics of optimal control design provides the theoretical foundation for this methodology. This foundation enables the inclusion of recovery costs within the resilience assessment approach, a unique capability for quantitative esilience assessment techniques. This paper describes the formulation of the optimal control problem for a set of representative infrastructure models. Thisexample demonstrates the importance of recovery costs in quantitative resilience analysis, and the increased capability provided by this approach's ability to discern between varying levels of resilience. © 2011 Inderscience Enterprises Ltd.

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Critical infrastructure resilience has become a national priority for the U. S. Department of Homeland Security. System resilience has been studied for several decades in many different disciplines, but no standards or unifying methods exist for critical infrastructure resilience analysis. Few quantitative resilience methods exist, and those existing approaches tend to be rather simplistic and, hence, not capable of sufficiently assessing all aspects of critical infrastructure resilience. This report documents the results of a late-start Laboratory Directed Research and Development (LDRD) project that investigated the development of quantitative resilience through application of control design methods. Specifically, we conducted a survey of infrastructure models to assess what types of control design might be applicable for critical infrastructure resilience assessment. As a result of this survey, we developed a decision process that directs the resilience analyst to the control method that is most likely applicable to the system under consideration. Furthermore, we developed optimal control strategies for two sets of representative infrastructure systems to demonstrate how control methods could be used to assess the resilience of the systems to catastrophic disruptions. We present recommendations for future work to continue the development of quantitative resilience analysis methods.

In this paper, we consider a boundary control problem governed by the two-dimensional Burgers equation for a configuration describing convective flow over an obstacle. Flows over obstacles are important as they arise in many practical applications. Burgers equations are also significant as they represent a simpler form of the more general Navier-Stokes momentum equation describing fluid flow. The aim of the work is to develop a reduced-order boundary control-oriented model for the system with subsequent nonlinear control law design. The control objective is to drive the full order system to a desired 2D profile. Reduced-order modeling involves the application of an L{sub 2} optimization based actuation mode expansion technique for input separation, demonstrating how one can obtain a reduced-order Galerkin model in which the control inputs appear as explicit terms. Controller design is based on averaging and center manifold techniques and is validated with full order numerical simulation. Closed-loop results are compared to a standard linear quadratic regulator design based on a linearization of the reduced-order model. The averaging/center manifold based controller design provides smoother response with less control effort and smaller tracking error.

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