Annulus-event-based fault detection for state-saturated nonlinear systems with time-varying delays. Issue 15 (October 2021)

• Record Type: Journal Article
• Authors: Chen, Weilu; Hu, Jun; Yu, Xiaoyang; Chen, Dongyan; Wu, Zhihui
• Is Part Of: Journal of the Franklin Institute. Volume 358:Issue 15(2021)
• Page Start: 8061
• Page End: 8084
• Publication Date: 2021-10
• Subjects: Science -- Periodicals; Technology -- Periodicals; Patents -- United States -- Periodicals; 505
• DOI: 10.1016/j.jfranklin.2021.08.006
• Languages: English
• ISSNs: 0016-0032

Abstract

Highlights: The annulus-event-based communication scheme is introduced for the purpose of avoiding unnecessary transmission of measurement outputs. A new fault detection scheme is given for saturated nonlinear systems with state saturations and time-varying delays. A new iterative linear matrix inequality algorithm is presented to deal with the obtained nonlinear matrix inequalities. Abstract: In this paper, the annulus-event-based fault detection method is proposed for a class of nonlinear systems subject to state saturation and time-varying delays. In particular, in order to save the network resources, a novel communication strategy called annulus-event-based triggering mechanism is considered. That is to say, the measurement output is sent to the filter only when the error between the measured value at the current moment and the data at the last transmission moment is within the prescribed triggering-annulus. Moreover, the system states at each instant are bounded by the convex hull via introducing a free matrix whose infinite norm is less than or equal to 1. Subsequently, sufficient conditions are obtained to ensure the global asymptotic stability and the H ∞ performance of the filtering error dynamics system, which are expressed in line with some nonlinear matrix inequalities that can be handled via the given iterative linear matrix inequality method. Finally, two numerical simulations are employed to illustrate the validity of the developed fault detection filtering algorithm.