Quantitative Resilience of Linear Driftless Systems

TL;DR

This paper introduces the concept of quantitative resilience for control systems, providing an efficient method to measure how much a system's performance degrades after actuator malfunctions, with applications in opinion dynamics and spacecraft control.

Contribution

It defines a new metric for resilience, and offers a novel geometric approach to compute it efficiently from a complex nested optimization problem.

Findings

The method reduces resilience computation to a single linear optimization problem.

Demonstrated on opinion dynamics and spacecraft trajectory control examples.

Provides a practical tool for assessing system robustness after actuator failures.

Abstract

This paper introduces the notion of quantitative resilience of a control system. Following prior work, we study systems enduring a loss of control authority over some of their 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 loss of control authority. However, after a malfunction a resilient system might be significantly slower to reach a target compared to its initial capabilities. We quantify this loss of performance through the new concept of quantitative resilience. We define this metric as the maximal ratio of the minimal times required to reach any target for the initial and malfunctioning systems. Na\"ive computation of quantitative resilience directly from the definition is a time-consuming task as it requires solving four nested, possibly nonlinear, optimization problems. The main technical contribution of this work is to provide an efficient method to compute quantitative resilience. Relying on control theory and on three novel geometric results we reduce the computation of quantitative resilience to a single linear optimization problem. We illustrate our method on two numerical examples: an opinion dynamics scenario and a trajectory controller for low-thrust spacecrafts.