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Towards a Theory of Control Architecture: A quantitative framework for layered multi-rate control

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arxiv 2401.15185 v1 pith:4HTFQKJS submitted 2024-01-26 math.OC cs.ROcs.SYeess.SY

classification math.OCcs.ROcs.SYeess.SY
keywords controldesigntheorynaturaltowardsarchitecturearchitecturesbacteria
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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.

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Cited by 2 Pith papers

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  1. Suboptimal and Reduced-Order MPC via Timescale Separation

    math.OC 2026-06 unverdicted novelty 6.0 of 10

    Framework for suboptimal reduced-order nonlinear MPC using timescale separation to guarantee recursive feasibility and exponential stability at sufficiently fast sampling rates.

  2. Capture, Shield, or Neutralize: Engagement-Aware Pursuit-Evasion

    eess.SY 2026-07 conditional novelty 5.0 of 10

    Minimax receding-horizon MPC plus a discrete CBF safety filter lets a pursuer swarm switch capture, perimeter defense, and neutralization modes by retuning shared costs and barrier weights alone.

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