Data‐driven analysis and control of periodic event‐triggered continuous‐time systems
Zi‐Jie Wei, Changyi Xu, K.Z. Liu, Wan‐Ling Qi, Xi‐Ming Sun
Abstract
Abstract 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.