Impact analysis of hidden faults in nonlinear control systems using output-to-output gain

TL;DR

This paper extends the output-to-output gain framework to nonlinear networked control systems, providing tools to analyze impact, detectability, and stability under faults and attacks.

Contribution

It introduces computationally efficient LMI conditions and frequency-domain tests for assessing impact and stability in nonlinear NCSs with quadratically constrained nonlinearities.

Findings

Provides explicit upper bounds on output-to-output gain for nonlinear systems.

Derives frequency-domain conditions for absolute stability, generalizing Yakubovich's criterion.

Extends impact analysis tools to nonlinear networked control systems with attack scenarios.

Abstract

Networked control systems (NCSs) are vulnerable to faults and hidden malfunctions in communication channels that can degrade performance or even destabilize the closed loop. Classical metrics in robust control and fault detection typically treat impact and detectability separately, whereas the output-to-output gain (OOG) provides a unified measure of both. While existing results have been limited to linear systems, this paper extends the OOG framework to nonlinear NCSs with quadratically constrained nonlinearities, considering false-injection attacks that can also manipulate sensor measurements through nonlinear transformations. Specifically, we provide computationally efficient linear matrix inequality conditions and complementary frequency-domain tests that yield explicit upper bounds on the OOG of this class of nonlinear systems. Furthermore, we derive frequency-domain conditions for absolute stability of closed-loop systems, generalizing the Yakubovich quadratic criterion.