This paper focuses on the need for a rigorous theory of layered control architectures (LCAs) for complex engineered and natural systems, such as power systems, communication networks, autonomous robotics, bacteria, and human sensorimotor control. All deliver extraordinary capabilities, but they lack a coherent theory of analysis and design, partly due to the diverse domains across which LCAs can be found. In contrast, there is a core universal set of control concepts and theory that applies very broadly and accommodates necessary domain-specific specializations. However, control methods are typically used only to design algorithms in components within a larger system designed by others, typically with minimal or no theory. This points towards a need for natural but large extensions of robust performance from control to the full decision and control stack. It is encouraging that the successes of extant architectures from bacteria to the Internet are due to strikingly universal mechanisms and design patterns. This is largely due to convergent evolution by natural selection and not intelligent design, particularly when compared with the sophisticated design of components. Our aim here is to describe the universals of architecture and sketch tentative paths towards a useful design theory.

翻译：本文聚焦于为复杂工程与自然系统（如电力系统、通信网络、自主机器人、细菌以及人类感觉运动控制）建立严谨的分层控制体系结构（Layered Control Architectures, LCAs）理论的需求。所有系统均展现出非凡的能力，但由于LCAs存在的领域跨度之大，它们缺乏统一的分析与设计理论。相比之下，存在一套核心的通用控制概念与理论，可广泛应用于各类场景，并容纳必要的领域特异性。然而，控制方法通常仅用于设计更大系统（由他人设计，且往往缺乏或仅有极少理论支撑）中组件的算法。这指向了一个需求：将鲁棒性能从控制领域自然且大规模地扩展至完整的决策与控制系统栈。令人振奋的是，从细菌到互联网的现有体系结构的成功，均源于惊人的通用机制与设计模式。这主要归因于自然选择驱动的趋同进化而非智能设计，尤其是与组件精密设计的成熟度相比。我们的目标是描述体系结构的通用性，并勾勒出迈向实用设计理论的初步路径。