Jamming-Resilient Synchronization of Networked Lagrangian Systems With Quantized Sampling Data

A wide range of cyber–physical systems can be modeled as Euler–Lagrange dynamics, whose inherent nonlinearities bring additional difficulties in the design and analysis of controllers for such systems. The objective of this article is to solve the jamming-resilient synchronization control problem of networked Lagrangian systems subject to unknown external disturbances, with the quantized sampling data. Under a jamming attack, a normal communication channel will be blocked with unknown frequencies and intervals. To achieve jamming attack resilience, a robust adaptive controller is proposed. Then a novel auxiliary system is designed for each subsystem over a directed network. By using the quantized sampling data from each subsystem and its neighbors, the jamming attack can be handled by an embedded single-integral subsystem. Sufficient conditions that are independent of the attack parameters are derived to guarantee the global stability of the closed-loop system. Compared with existing jamming-resilient methods, the proposed approach is concise and resilient to any jamming attacks with bounded frequencies and durations.