  This article explains the distinctions between robustness and resilience in
control systems. 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, it delves
into contextual dualism and interactionism, and introduces 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 formalization through game-theoretic frameworks are
necessary. The exploration extends to system-of-systems resilience and various
mechanisms, including the integration of AI techniques and non-technical
solutions, like cyber insurance, to achieve comprehensive resilience in control
systems. As we approach 2030, the systems and control community is at the
opportune moment to lay 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 cyber insecurity.
