AI 中文总结
研究在信息有限时生物及工程系统对随机系统的反馈控制，推导信息率下限，得出性能-信息帕累托前沿，给出特定系统最优控制协议，通过非线性粒子定位等应用展示结果。
AI 中文摘要
跨尺度的生物系统以及许多工程问题，必须在信息有限的情况下控制有噪声的系统。在此，我们研究随机系统的信息受限反馈控制以实现目标稳态，并推导出从受控系统到控制器的信息率下限。该框架使我们能够获得广泛的有限信息控制问题的性能-信息帕累托前沿。对于具有与状态无关的被动动力学的系统，该界限可由一个明确的最优控制协议达到饱和，该协议以概率方式使被动动力学时间反转。我们通过将这些结果应用于非线性粒子定位、微生物导航和实验实现的信息引擎来展示。
英文摘要
Biological systems across scales, along with many engineering problems, must control noisy systems with limited information. Here we study information-limited feedback control of stochastic systems to achieve target steady states, and derive a lower bound on the information rate from controlled system to controller. This framework allows us to obtain performance-information Pareto frontiers for wide-ranging control problems with limited information. For systems with state-independent passive dynamics, the bound is saturated by an explicit optimal control protocol which probabilistically time-reverses the passive dynamics. We showcase these results through applications to nonlinear particle localization, microbial navigation, and experimentally realized information engines.
Comments9 pages, 5 figures, + 14 pages SI
