Quantitative Resilience of Generalized Integrators
Jean-Baptiste Bouvier, Kathleen Xu, Melkior Ornik

TL;DR
This paper introduces a new method to efficiently quantify how much a control system’s performance degrades after actuator malfunctions, using geometric insights to simplify complex optimization problems.
Contribution
It presents a novel approach to compute quantitative resilience in control systems with multiple integrators, reducing complex problems to linear optimization.
Findings
Method efficiently computes resilience for systems with multiple integrators.
Application to spacecraft trajectory control demonstrates practical utility.
UAV example shows the method's effectiveness in real-world scenarios.
Abstract
To design critical systems engineers must be able to prove that their system can continue with its mission even after losing control authority over some of its actuators. Such a malfunction results in actuators producing possibly undesirable inputs over which the controller has real-time readings but no control. By definition, a system is resilient if it can still reach a target after a partial loss of control authority. However, after such a malfunction, a resilient system might be significantly slower to reach a target compared to its initial capabilities. To quantify this loss of performance we introduce the notion of quantitative resilience as the maximal ratio of the minimal times required to reach any target for the initial and malfunctioning systems. Naive computation of quantitative resilience directly from the definition is a complex task as it requires solving four nested,…
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Taxonomy
TopicsAdvanced Control Systems Optimization · Fault Detection and Control Systems
