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

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.