超越吸引力盆地：量化自然动态的鲁棒性
Beyond Basins of Attraction: Quantifying Robustness of Natural Dynamics
摘要：
适当地设计一个系统，表现出良好的自然动态可以大大简化设计或学习的控制策略。然而，目前还不清楚什么是有利的自然动态，以及如何量化其影响。大多数简单的步行和跑步模型的研究都集中在被动极限环的吸引盆地和自稳定的概念。相反，我们强调超越吸引力的重要性。我们提出了一种基于生存理论的方法来量化状态-动作空间中的鲁棒集。这些集是有效的所有鲁棒控制策略的家庭，这使我们能够量化的鲁棒性固有的自然动态之前，设计的控制策略或指定的控制目标。我们说明我们的配方使用弹簧质量模型，简单的低维模型的运行系统。然后，我们展示了一个例子的应用程序，通过优化的鲁棒性的模拟平面monoped，使用无梯度优化方案。这两种情况下的研究结果在非线性有效刚度提供更多的鲁棒性。
英文摘要：
Properly designing a system to exhibit favorable natural dynamics can greatly simplify designing or learning the control policy. However, it is still unclear what constitutes favorable natural dynamics and how to quantify its effect. Most studies of simple walking and running models have focused on the basins of attraction of passive limit-cycles and the notion of self-stability. We instead emphasize the importance of stepping beyond basins of attraction. We show an approach based on viability theory to quantify robust sets in state-action space. These sets are valid for the family of all robust control policies, which allows us to quantify the robustness inherent to the natural dynamics before designing the control policy or specifying a control objective. We illustrate our formulation using spring-mass models, simple low dimensional models of running systems. We then show an example application by optimizing robustness of a simulated planar monoped, using a gradient-free optimization scheme. Both case studies result in a nonlinear effective stiffness providing more robustness.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
