Data-driven analysis and control of periodic event-triggered continuous-time systems

This article is concerned with data-driven analysis and controller design for continuous-time sampled-data systems. The linear system considered in this paper is controlled under the periodic event-triggering transmission mechanism. Firstly, the periodic event-triggered control (PETC) systems are modeled and analyzed by the time-delay approach. And model-based stability conditions are presented by invoking the Lyapunov stability approach. Secondly, based on the model-based conditions and a popular data-based representation, data-based stability criteria are deduced by using only noisy data. The stability criteria guarantee the stability properties robustly for all unknown systems consistent with the measured data. The data-driven estimation of the maximum detecting interval (MDI) is also obtained directly without model knowledge. Beyond that, the data-based method for the controller design as well as computing a possibly large MDI under various triggering parameters is put forth. Finally, the effectiveness of the proposed methods is demonstrated by the numerical simulation and the hardware-in-the-loop (HIL) experiment.