论文标题
使用控制屏障功能的安全问题明确解决方案
Explicit Solutions for Safety Problems Using Control Barrier Functions
论文作者
论文摘要
控制屏障函数方法已被广泛用于安全控制器合成。通过解决在线凸二次编程问题，可以在状态空间中隐式合成最佳的安全控制器。由于该解决方案是唯一的，因此从状态空间到控制输入的映射是注入性的，从而使我们能够评估基本关系。在本文中，我们旨在将安全控制定律明确合成，这是该州的非线性控制型系统的函数，具有有限的控制能力。我们建议将在线二次编程问题转换为一个将状态视为参数的离线参数化优化问题。如果程序可行，则获得的显式安全控制器被证明是在分区状态空间上连续函数的零件。我们通过解决基于参数化的自适应控制屏障功能问题来解决不可行的情况。广泛的仿真结果显示了状态空间分区和控制器属性。
The control Barrier function approach has been widely used for safe controller synthesis. By solving an online convex quadratic programming problem, an optimal safe controller can be synthesized implicitly in state-space. Since the solution is unique, the mapping from state-space to control inputs is injective, thus enabling us to evaluate the underlying relationship. In this paper we aim at explicitly synthesizing a safe control law as a function of the state for nonlinear control-affine systems with limited control ability. We propose to transform the online quadratic programming problem into an offline parameterized optimisation problem which considers states as parameters. The obtained explicit safe controller is shown to be a piece-wise Lipschitz continuous function over the partitioned state space if the program is feasible. We address the infeasible cases by solving a parameterized adaptive control Barrier function-based quadratic programming problem. Extensive simulation results show the state-space partition and the controller properties.
