论文标题
基于控制障碍功能的半明确程序（CBF-SDP）：具有相对程度的动态系统的强大安全控制两个安全指数
Control Barrier Functions-based Semi-Definite Programs (CBF-SDPs): Robust Safe Control For Dynamic Systems with Relative Degree Two Safety Indices
论文作者
论文摘要
在本文草案中，我们考虑了安全控制系统安全索引或（控制屏障函数（松散））相对程度等于两个的问题的问题。我们考虑参数仿射非线性动态系统，并假设参数不确定性是统一的，并且已知A-Priori或通过估算器/参数适应定律在线更新。在这种不确定性下，通常的CBF-QP安全控制方法采用了强大的优化问题的形式。不等式约束的右侧和左侧都取决于未知参数。通过给定的不确定性表示，CBF-QP安全控制最终是凸半无限问题的问题。使用两种不同的哲学，一种基于弱二元性，另一个基于无损S-生产的哲学，我们得出了此强大的CBF-QP问题的相同的SDP公式。因此，我们表明，以已知参数不确定性计算安全控制的问题可以作为可处理的凸问题提出并在线解决。 （这是正在进行的工作）。
In this draft article, we consider the problem of achieving safe control of a dynamic system for which the safety index or (control barrier function (loosely)) has relative degree equal to two. We consider parameter affine nonlinear dynamic systems and assume that the parametric uncertainty is uniform and known a-priori or being updated online through an estimator/parameter adaptation law. Under this uncertainty, the usual CBF-QP safe control approach takes the form of a robust optimization problem. Both the right hand side and left hand side of the inequality constraints depend on the unknown parameter. With the given representation of uncertainty, the CBF-QP safe control ends up being a convex semi-infinite problem. Using two different philosophies, one based on weak duality and another based on the Lossless s-procedure, we arrive at identical SDP formulations of this robust CBF-QP problem. Thus we show that the problem of computing safe controls with known parametric uncertainty can be posed as a tractable convex problem and be solved online. (This is work in progress).
