Network-based Fault Detection of Servomechanism Systems with Packet Dropouts

• Published in: 2020 International Conference on Culture-oriented Science & Technology (ICCST) pp. 181 - 186
• Main Authors: Chen, Pengcheng, He, Zhitao, Zhang, Hang, Zhang, Dan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2020
• Subjects: Automation; Average dwell time; Electrical fault detection; Fault detection; Lyapunov methods; Packet dropouts; Servomechanism systems; Servomechanisms; Switched systems; Switches
• DOI: 10.1109/ICCST50977.2020.00041

In this paper, we address the fault detection problem of the servomechanism systems with stochastic packet dropouts, where a fault detection filter is devised to generate the residual signal to detect the fault. Firstly, a switched system equation is used to model the dynamics of the position servomechanism system, and the fault detection problem subject to packet dropouts is transformed into an exponential H ∞ filtering problem. Then, by applying Lyapunov stability theory and average dwell time approach, several sufficient criteria are proposed to ensure that the filtering error system is exponentially stable in the mean-square sense with a prescribed H ∞ performance level and the filter parameters of the servomechanism system are derived by solving some linear matrix inequalites(LMIs). Finally, a simulation case is presented to affirm the effectiveness of the proposed results.