Abstract
Although robustness often is cited as a desirable property of a system, a widely-accepted approach for quantifying it remains elusive. Informally, a system is robust if it avoids the downside consequences associated with uncertainty or perturbations. Prior approaches to quantifying robustness rely on the standard deviation of system responses or the expected ratio of performance under perturbation to nominal performance. Because the principal usefulness of any system metric is to inform decisions about the design of that system, we turn to rigorous decision theory for guidance on how to deal with the concept of robustness. We find that existing proposals for robustness quantification are inconsistent with accepted theory for rational decision making. Rather than propose an alternative quantification scheme, we argue that fundamentally there is no need to quantify robustness as an independent figure of merit. Instead, systems engineers can make decisions that favor system robustness using established methods based on expected utility theory. A key to this is formulating the decision problem in terms of fundamental objectives rather than means objectives. One's preference to favor robustness is associated with being risk averse over the fundamental objectives and is captured by using a concave utility function.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.