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arXiv 2005.06418eess.SYcs.SYmath.OC
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具有输入时滞的采样数据系统的控制障碍函数

Control Barrier Functions for Sampled-Data Systems with Input Delays

Andrew Singletary, Yuxiao Chen, Aaron D. Ames

摘要:

本文认为,一般的问题,理论上安全的控制器过渡到硬件。具体地说,我们探讨应用控制障碍函数(CBF)的采样数据系统:系统不断发展,但其控制行动是在离散的时间步长计算。虽然这种模型公式比其连续对应物更不常用,但它更准确地模拟了实践中大多数控制系统的现实,使安全保证更具影响力。在这种情况下,我们证明了强大的零阶保持控制器以及状态不确定性的集合不变性,而不需要明确计算任何控制不变集。然后,它表明,可以利用这个配方来解决在这个系统中的输入延迟,其结果是CBF的约束,是仿射的输入。结果表明,在一个不稳定的赛格威机器人系统的实时高保真仿真。

英文摘要:

This paper considers the general problem of transitioning theoretically safe controllers to hardware. Concretely, we explore the application of control barrier functions (CBFs) to sampled-data systems: systems that evolve continuously but whose control actions are computed in discrete time-steps. While this model formulation is less commonly used than its continuous counterpart, it more accurately models the reality of most control systems in practice, making the safety guarantees more impactful. In this context, we prove robust set invariance with respect to zero-order hold controllers as well as state uncertainty, without the need to explicitly compute any control invariant sets. It is then shown that this formulation can be exploited to address input delays in this system, with the result being CBF constraints that are affine in the input. The results are demonstrated in a high-fidelity simulation of an unstable Segway robotic system in real-time.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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