论文标题
具有控制屏障功能的安全关键系统的近似最佳控制
Approximate Optimal Control for Safety-Critical Systems with Control Barrier Functions
论文作者
论文摘要
控制障碍功能（CBF）已成为在安全关键控制系统中执行设置不变性的流行工具。在确保安全性的同时，大多数CBF方法都是近视方法，因为它们在每个时间步骤而不是在很长一段时间内都解决了优化问题。这种方法可能会使系统变得太接近不安全的集合，在这种情况下，优化问题可能变得不可行。这些问题中的一些可以通过将放松变量引入优化问题来缓解；但是，这损害了融合到所需的平衡点。为了应对这些挑战，我们针对安全关键控制问题开发了一种近似的最佳方法，其中违反安全限制的成本直接嵌入了价值函数中。我们表明我们的方法能够保证安全和收敛到所需的平衡。最后，我们通过数值示例将方法的性能与传统二次编程方法的性能进行了比较。
Control Barrier Functions (CBFs) have become a popular tool for enforcing set invariance in safety-critical control systems. While guaranteeing safety, most CBF approaches are myopic in the sense that they solve an optimization problem at each time step rather than over a long time horizon. This approach may allow a system to get too close to the unsafe set where the optimization problem can become infeasible. Some of these issues can be mitigated by introducing relaxation variables into the optimization problem; however, this compromises convergence to the desired equilibrium point. To address these challenges, we develop an approximate optimal approach to the safety-critical control problem in which the cost of violating safety constraints is directly embedded within the value function. We show that our method is capable of guaranteeing both safety and convergence to a desired equilibrium. Finally, we compare the performance of our method with that of the traditional quadratic programming approach through numerical examples.
