Infrastructure resilience assessment through control design

Abstract

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.

Optimal recovery sequencing for critical infrastructure resilience assessment.

“…These costs are calculated as Vugrin, et al's (2010) resilience cost approach lends itself nicely to mathematical formulations utilized for the development of optimal feedback control laws. Vugrin, et al (2009b) investigated the development of quantitative CIR analysis through the application of control methods. Vugrin, et al (2009b) concluded that for a particular subset of infrastructure models, optimal feedback control design is a promising approach for identification of optimal recovery strategies.…”

“…Vugrin, et al (2009b) investigated the development of quantitative CIR analysis through the application of control methods. Vugrin, et al (2009b) concluded that for a particular subset of infrastructure models, optimal feedback control design is a promising approach for identification of optimal recovery strategies. Specifically, Vugrin, et al (2009b) demonstrated application of linear quadratic regulator (LQR) feedback control methods on a set linear models with continuous spatial domains for resilience assessment.…”

“…Vugrin, et al (2009b) concluded that for a particular subset of infrastructure models, optimal feedback control design is a promising approach for identification of optimal recovery strategies. Specifically, Vugrin, et al (2009b) demonstrated application of linear quadratic regulator (LQR) feedback control methods on a set linear models with continuous spatial domains for resilience assessment. However, Vugrin, et al (2009b) also noted that many infrastructure models have nonlinearities and discrete decentralized components.…”

“…Specifically, Vugrin, et al (2009b) demonstrated application of linear quadratic regulator (LQR) feedback control methods on a set linear models with continuous spatial domains for resilience assessment. However, Vugrin, et al (2009b) also noted that many infrastructure models have nonlinearities and discrete decentralized components. Traditional feedback control design is generally not applicable to these types of models, and Vugrin, et al recommended the further investigation into more traditional optimization approaches for generalizing the optimal resilience problem.…”

Modeling Resiliency and Its Essential Components for Cyberphysical Systems

“…Similar views have been expressed by researchers at the Idaho National Laboratory [11] and others. Consequently, Vugrin et al, at SANDIA [34] state that "the cybersecurity community has voiced the opinion that cybersecurity strategies must expand beyond the protection-centric focus to incorporate cyber resilience principles." This has been advocated even earlier, by a national panel of researchers [35], stating that in case of a disruption such as an imminent security breach, what "cyberphysical systems require is either reconfiguration to reacquire the needed resources automatically or graceful degradation if they are not available.…”