发表机构
Klipsch School of Electrical and Computer Engineering, New Mexico State University; Department of Aerospace Engineering, Embry-Riddle Aeronautical University（新墨西哥州立大学克利普什电气与计算机工程学院; 安柏瑞德航空航天大学航空航天工程系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对智能系统时变安全失效问题，提出结合在线递减SVM的时变CBF安全过滤框架，通过VTOL仿真验证其可在控制权限下降时保障安全且避免障碍突变。
AI 中文摘要
任务关键型智能系统通常在时变限制下运行，这些限制会降低控制权限并改变可接受的安全操作范围。在这种情况下，在标称条件下学习到的安全证书可能会随着系统能力的变化而失效。为应对这一挑战，本文提出一种感知退化的、基于数据的安全过滤框架，该框架从数据中学习安全集、在线更新安全集，并通过时变控制障碍函数（CBF）强制执行所得的学习障碍。首先使用径向基函数（RBF）核支持向量机（SVM）从运行数据中学习标称安全范围，其决策函数作为初始CBF候选。为捕捉能力导致的安全集收缩，开发了连续时间递减SVM更新律，使选定的支持向量系数根据退化信号减小。随后引入同伦平滑SVM-CBF，以避免主动集转换期间学习障碍的不连续变化。所得时变学习障碍在退化输入约束下通过基于二次规划的安全过滤执行。建立了学习到的时变安全集的前向不变性和安全过滤的递归可行性。在垂直起降（VTOL）模型上的仿真结果表明，所提方法在控制权限降低时能保持安全，并在安全集收缩期间避免了突然的障碍切换效应。
英文摘要
Mission-critical intelligent systems often operate under time-varying limitations that reduce control authority and change the admissible safe operating envelope. In such settings, a safety certificate learned under nominal conditions may become invalid as system capability changes. To address this challenge, this paper proposes a degradation-aware, data-driven safety-filtering framework that learns a safe set from data, updates it online, and enforces the resulting learned barrier through a time-varying control barrier function (CBF). A nominal safe envelope is first learned from operational data using a radial basis function (RBF)-kernel support vector machine (SVM), whose decision function serves as the initial CBF candidate. To capture capability-induced safe-set contraction, a continuous-time decremental SVM update law is developed so that selected support-vector coefficients are reduced according to a degradation signal. A homotopy-smoothed SVM-CBF is then introduced to avoid discontinuous changes in the learned barrier during active-set transitions. The resulting time-varying learned barrier is enforced using a quadratic-program-based safety filter under degraded input constraints. Forward invariance of the learned time-varying safe set and recursive feasibility of the safety filter are established. Simulation results on a vertical takeoff and landing (VTOL) model show that the proposed method maintains safety under reduced control authority and avoids abrupt barrier-switching effects during safe-set contraction.
Comments14 pages, 9 figures
