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.

翻译：本文阐释了控制系统中的鲁棒性与韧性之间的区别。韧性面临一系列独特的挑战，为设计优先考虑韧性而非鲁棒性的反馈系统、网络和机器的控制器提出了新问题。通过一个三阶段模型探索了韧性的概念，强调了对弹性事件进行主动准备和自动化响应的必要性。首先使用一个玩具模型来说明韧性与鲁棒性之间的权衡。随后深入探讨了情境二元论和互动主义，并引入博弈论范式作为统一框架来整合韧性与鲁棒性。本文最后讨论了鲁棒性与韧性之间的相互作用，指出需要建立一套全面的韧性理论、量化指标，并通过博弈论框架进行形式化。探索还扩展到系统之系统的韧性及多种机制，包括集成人工智能技术以及网络保险等非技术解决方案，以实现控制系统的全面韧性。在迈向2030年之际，系统与控制学界正处在通过联结反馈控制理论、博弈论和学习理论为韧性奠定科学基础的恰当时机。韧性控制系统将提升整体生活质量，推动韧性社会的发展，并在气候变化、冲突和网络安全风险等全球性挑战中产生社会层面的影响。