Infrastructure resilience assessment through control design

Infrastructure resilience is a priority for homeland security in many nations around the globe. This paper describes a new approach for quantitatively 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 resilience assessment techniques. This paper describes the formulation of the optimal control problem for a set of representative infrastructure models. This example 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.

[1]  J. Gibson.  Linear-Quadratic Optimal Control of Hereditary Differential Systems: Infinite Dimensional Riccati Equations and Numerical Approximations , 1983 .

[2]  J. Doyle,et al.  Robust and optimal control , 1995, Proceedings of 35th IEEE Conference on Decision and Control.

[3]  H. Banks,et al.  Hereditary Control Problems: Numerical Methods Based on Averaging Approximations , 1978 .

[4]  Michael K. Reiter,et al.  Homeland Security , 2004, IEEE Internet Comput..

[5]  Emanuel Todorov,et al.  Optimal Control Theory , 2006 .

[6]  A. Rose,et al.  Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions , 2005 .

[7]  Michel Bruneau,et al.  A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities , 2003 .

[8]  Drake E. Warren,et al.  A Framework for Assessing the Resilience of Infrastructure and Economic Systems , 2010 .

[9]  Thomas A. Johnson,et al.  Homeland Security Presidential Directive-1 , 2007 .

[10]  I. G. Rosen,et al.  Convergence of Galerkin approximations for operator Riccati equations—A nonlinear evolution equation approach , 1991 .

[11]  Stephanie E. Chang,et al.  Measuring Improvements in the Disaster Resilience of Communities , 2004 .

[12]  B. R. Noack.  Turbulence, Coherent Structures, Dynamical Systems and Symmetry , 2013 .

[13]  Ronald E. Fisher,et al.  Constructing a resilience index for the Enhanced Critical Infrastructure Protection Program , 2010 .

[14]  Athanasios C. Antoulas,et al.  Approximation of Large-Scale Dynamical Systems , 2005, Advances in Design and Control.

[15]  Franz Kappel,et al.  Approximation of LQR-Problems for Delay Systems: A Survey , 1991 .

[16]  J Swanson,et al.  Business Dynamics—Systems Thinking and Modeling for a Complex World , 2002, J. Oper. Res. Soc..