Event-based joint state and fault estimation: The envelope-constrained H∞ criterion

Licheng Wang and Hui Chen

Applied Mathematics and Computation, 2022, vol. 419, issue C

Abstract: In this paper, the joint state and fault estimation problem is investigated for a class of discrete time-varying systems under the dynamic event-triggering mechanism. The actuator fault and the sensor fault are, respectively, considered in the state and measurement equations where only the changing rate of the actuator fault is needed. The dynamic event-triggering scheme is used to decrease unnecessary transmissions from the sensor to the estimator. To facilitate the joint estimator design, a novel descriptor system model is constructed by aggregating the system state and the sensor fault. The main aim of the addressed problem is to design a joint estimator to ensure that the estimation error dynamics simultaneously achieves the finite-horizon H∞ performance and the envelope constraint. Sufficient conditions are provided to obtain the desired joint estimator parameters by solving a series of recursive matrix inequalities. Finally, a numerical simulation example is given to demonstrate the effectiveness of the proposed estimation method. The major novelty of this study is that we make one of the very first few attempts to deal with the multi-objective joint state and fault estimation issue under the dynamic event-trigging transmission mechanism.

Keywords: Fault estimation; Envelope constraints; Dynamic event-triggering mechanism; Finite-horizon H∞ performance (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300321009565
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:419:y:2022:i:c:s0096300321009565

DOI: 10.1016/j.amc.2021.126873

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().