This letter presents a constrained control framework that integrates Explicit Reference Governors (ERG) with Control Barrier Functions (CBF) to ensure recursive feasibility without online optimization. We formulate the reference update as a virtual control input for an augmented system, governed by a smooth barrier function constructed from the softmin aggregation of Dynamic Safety Margins (DSMs). Unlike standard CBF formulations, the proposed method guarantees the feasibility of safety constraints by design, exploiting the forward invariance properties of the underlying Lyapunov level sets. This allows for the derivation of an explicit, closed-form reference update law that strictly enforces safety while minimizing deviation from a nominal reference trajectory. Theoretical results confirm asymptotic convergence, and numerical simulations demonstrate that the proposed method achieves performance comparable to traditional ERG frameworks.

翻译：本文提出一种结合显式参考调节器（ERG）与控制障碍函数（CBF）的约束控制框架，无需在线优化即可保证递归可行性。我们将参考更新构建为增广系统的虚拟控制输入，该虚拟输入受由动态安全裕度（DSM）的softmin聚合构建的光滑障碍函数约束。与传统CBF公式不同，所提方法通过设计保证安全约束的可行性，利用了底层李雅普诺夫水平集的前向不变性特性。由此推导出显式闭式参考更新律，该更新律在严格保证安全性的同时最小化与标称参考轨迹的偏差。理论结果证明了渐进收敛性，数值仿真表明该方法可达到与传统ERG框架相当的性能。