提出鲁棒安全控制方法，应对动态不确定性下的系统安全问题。
Disturbance-Robust Backup Control Barrier Functions: Safety Under Uncertain Dynamics
- 基于扰动边界构建随时间扩展的范数球管，实时保证安全
- 在双积分器和刚体航天器旋转问题中验证了安全性与有效性
- 适合存在未建模扰动的安全关键控制系统设计
获取控制不变集对具有控制屏障函数（CBFs）的安全关键控制至关重要，但对复杂非线性系统和约束而言并不容易。备份控制屏障函数可通过检查已知备份控制律下系统的演化（或流动）在线构造此类集合，计算上可行。然而，对于存在未建模扰动的系统，该流动无法直接计算，现有方法难以确保此类场景下的安全性。为填补这一空白，我们利用名义系统与扰动系统流动的上下界，通过确保围绕名义系统演化路径的扩展范数球管的安全性，在线计算一个前向不变集。我们证明该集合可生成鲁棒控制约束，通过提出的扰动鲁棒备份控制屏障函数（DR-bCBF）解决方案，保证扰动系统的安全性。所提框架在仿真中得到验证，应用于带有速率约束的双积分器问题和刚体航天器姿态旋转问题。
原文摘要 · Abstract (English)
Obtaining a controlled invariant set is crucial for safety-critical control with control barrier functions (CBFs) but is non-trivial for complex nonlinear systems and constraints. Backup control barrier functions allow such sets to be constructed online in a computationally tractable manner by examining the evolution (or flow) of the system under a known backup control law. However, for systems with unmodeled disturbances, this flow cannot be directly computed, making the current methods inadequate for assuring safety in these scenarios. To address this gap, we leverage bounds on the nominal and disturbed flow to compute a forward invariant set online by ensuring safety of an expanding norm ball tube centered around the nominal system evolution. We prove that this set results in robust control constraints which guarantee safety of the disturbed system via our Disturbance-Robust Backup Control Barrier Function (DR-bCBF) solution. The efficacy of the proposed framework is demonstrated in simulation, applied to a double integrator problem and a rigid body spacecraft rotation problem with rate constraints.
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