Data-Driven $\mathcal {L}_{2}$-Stability Analysis for Dynamic Event-Triggered Networked Control Systems: A Hybrid System Approach

Abstract

This paper addresses the problem of data-driven control and stability analysis for networked control systems (NCSs). The systems considered in this paper are assumed to be linear with unknown system matrices and bounded external disturbance. Firstly, a static state-feedback controller is derived directly from noisy data in the absence of network. Secondly, the NCSs including a dynamic event-triggering mechanism (DETM) and time-varying transmission delays are modeled as a hybrid system. Then the <inline-formula><tex-math notation="LaTeX">$\mathcal {L}_{2}$</tex-math></inline-formula>-stability conditions for the hybrid system are established by using the Lyapunov stability approach. Thirdly, by combining the model-based conditions and the parametric representation of the unknown system matrices, data-based stability conditions are derived. Based on the methods proposed in this paper, many well-established model-based theorems can be readily applied to the unknown linear systems. Finally, the proposed theories are verified on a turbofan engine hardware-in-the-loop (HIL) simulation platform.