论文标题
使用控制Lyapunov和障碍功能的自适应稳健二次程序
Adaptive Robust Quadratic Programs using Control Lyapunov and Barrier Functions
论文作者
论文摘要
本文使用控制lyapunov和屏障功能为非线性系统提供基于自适应的鲁棒二次程序（QP）控制，但受到时间变化和状态依赖性不确定性的影响。提出了一种自适应估计定律，以估计不确定性的端度值，并具有可预测的估计误差界限。然后使用估计的不确定性和误差界限来制定稳健的QP，这确保实际的不确定系统不会违反由控制屏障功能定义的安全约束。另外，通过减少估计抽样时间，可以系统地改善不确定性估计的准确性，随后导致了配方稳定QP的保守性。在模拟自适应巡航控制问题以及与现有方法的比较中，对所提出的方法进行了验证。
This paper presents adaptive robust quadratic program (QP) based control using control Lyapunov and barrier functions for nonlinear systems subject to time-varying and state-dependent uncertainties. An adaptive estimation law is proposed to estimate the pointwise value of the uncertainties with pre-computable estimation error bounds. The estimated uncertainty and the error bounds are then used to formulate a robust QP, which ensures that the actual uncertain system will not violate the safety constraints defined by the control barrier function. Additionally, the accuracy of the uncertainty estimation can be systematically improved by reducing the estimation sampling time, leading subsequently to reduced conservatism of the formulated robust QP. The proposed approach is validated in simulations on an adaptive cruise control problem and through comparisons with existing approaches.
