Problem
Research questions and friction points this paper is trying to address.
autonomous systems
safety
stability
resilience indicators
critical slowing down
Indicators of resilience for autonomous control systems
🤖 AI Summary
研究通过设计通用韧性指标来预测非线性控制系统稳定性损失，利用机器人系统模拟和四旋翼飞行器实验验证了该方法的有效性。
📝 Abstract
As modern societies rely more on autonomous systems to facilitate daily life, assuring their safe operation is paramount. Naturally, there are many techniques available to predict and prevent system failures. However, the safety afforded by such schemes may become misaligned with the true system, which can change in unexpected ways - from partial faults to natural wear-and-tear - that subtly degrade its stability. The implications that such subtle changes have on autonomous system stability can be observed through generic indicators of resilience derived from critical slowing down, popular for anticipating catastrophic tipping points in natural systems. Here, we show how one can systematically design these generic indicators for nonlinear control systems and show how these can reflect loss of stability though simulations of canonical robotic systems wherein their proximity to instability is manipulated directly. These results are affirmed through real-world flight experiments of a quadrotor that is nudged towards instability by progressively damaging its propeller blades. Our results show that the implications of degraded resilience on closed-loop stability are evident well before they appear, for which the indicators of resilience derived here can provide an early warning.
Innovation
Methods, ideas, or system contributions that make the work stand out.
resilience indicators
nonlinear control systems
critical slowing down
stability loss
early warning
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