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Extent-compatible control barrier functions

机译:范围兼容控制屏障功能

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摘要

Safety requirements in dynamical systems are commonly enforced with set invariance constraints over a safe region of the state space. Control barrier functions, which are Lyapunov-like functions for guaranteeing set invariance, are an effective tool to enforce such constraints and guarantee safety when the system is represented as a point in the state space. In this paper, we introduce extent-compatible control barrier functions as a tool to enforce safety for the system explicitly accounting for its volume (extent) within an ambient workspace. In order to implement the extent-compatible control barrier functions framework, we first propose a sum-of-squares optimization program that is solved pointwise in time to ensure safety. Since sum-of-squares programs can be computationally prohibitive, we next propose an approach that instead considers a finite number of points sampled on the extent boundary. The result is a quadratic program for guaranteed safety that retains the computational advantage of traditional barrier functions. While this alternative is generally more conservative than the sum-of-squares approach, we show that conservatism is reduced by increasing the number of sampled points. Simulation and robotic implementation results are provided. (C) 2021 Elsevier B.V. All rights reserved.
机译:动力系统中的安全要求通常在状态空间的安全区域上通过集合不变性约束来实现。控制障碍函数是保证集合不变性的类Lyapunov函数,当系统被表示为状态空间中的一个点时,控制障碍函数是一种有效的工具,可以强制执行此类约束并保证安全性。在本文中,我们引入了与范围兼容的控制屏障功能,作为一种工具,以明确说明系统在环境工作空间中的体积(范围)来加强系统的安全性。为了实现范围兼容控制屏障功能框架,我们首先提出了一个平方和优化程序,该程序在时间上逐点求解,以确保安全。由于平方和程序在计算上可能是禁止的,我们接下来提出一种方法,该方法考虑在范围边界上采样的有限个点。结果是一个保证安全的二次规划,保留了传统屏障函数的计算优势。虽然这种方法通常比平方和方法更保守,但我们表明,通过增加采样点的数量,保守性会降低。给出了仿真和机器人实现结果。(c)2021爱思唯尔B.V.保留所有权利。

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