Disentangling Resilience From Robustness: Contextual Dualism, Interactionism, and Game-Theoretic Paradigms

This article explains the distinctions between robustness and resilience in control systems (see “Summary”). Resilience confronts a distinct set of challenges, posing new ones for designing controllers for feedback systems, networks, and machines that prioritize resilience over robustness. The concept of resilience is explored through a three-stage model, emphasizing the need for a proactive preparation and automated response to elastic events. A toy model is first used to illustrate the tradeoffs between resilience and robustness. Then, we delve into contextual dualism and interactionism and introduce game-theoretic paradigms as a unifying framework to consolidate resilience and robustness. The article concludes by discussing the interplay between robustness and resilience, suggesting that a comprehensive theory of resilience and quantification metrics and also formalization through game-theoretic frameworks are necessary. The exploration extends to system-of-systems resilience and various mechanisms, including the integration of artificial intelligence (AI) techniques and nontechnical solutions, like cyberinsurance, to achieve comprehensive resilience in control systems. As we approach 2030, the systems and control community is at the opportune moment to lay the scientific foundations of resilience by bridging feedback control theory, game theory, and learning theory. Resilient control systems will enhance overall quality of life, enable the development of a resilient society, and create a societal-scale impact amid global challenges, such as climate change, conflicts, and cyberinsecurity.