Joint state and actuator fault estimation for networked systems under improved accumulation-based event-triggered mechanism

Jiyue Guo; Hongjian Liu; Jun Hu; Baoye Song

doi:10.1016/j.isatra.2022.04.011

Joint state and actuator fault estimation for networked systems under improved accumulation-based event-triggered mechanism

ISA Trans. 2022 Aug:127:60-67. doi: 10.1016/j.isatra.2022.04.011. Epub 2022 Apr 14.

Authors

Jiyue Guo¹, Hongjian Liu², Jun Hu³, Baoye Song¹

Affiliations

¹ College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China.
² School of Mathematics and Physics, Anhui Polytechnic University, Wuhu 241000, China; Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment, Ministry of Education, Anhui Polytechnic University, Wuhu 241000, China; Artificial Intelligence Energy Research Institute, Northeast Petroleum University, Daqing 163318, China. Electronic address: hjliu1980@gmail.com.
³ Department of Mathematics, Harbin University of Science and Technology, Harbin 150080, China; School of Engineering, University of South Wales, Pontypridd CF37 1DL, UK.

PMID: 35491254
DOI: 10.1016/j.isatra.2022.04.011

Abstract

The joint state and actuator fault estimation problem is investigated in this paper for a type of networked systems subject to loss of the actuator effectiveness (LAE). A so-called improved accumulation-based event-triggered mechanism (ETM) is used to regulate the transmission of signals between the sensors and the estimator for the purpose of communication resource saving. Compared with the traditional ETM schemes, such accumulation-based ETM is robust against the "undesired" abrupt changes of signals (which would occur due to certain big noises). Different from the integral-based ETM for continuous-time systems, the improved accumulation-based ETM proposed in this paper is a "weighted" ETM, where a given weight coefficient is employed to "balance" the weights of output measurements in different time instants. The multiplicative LAE is described by an unknown diagonal matrix. The object of this paper is to design a remote estimator such that both the fault signals and system states can be simultaneously estimated in the sense of minimizing an upper bound of the corresponding estimation error covariance at each sampling instant. First, the upper bound of the estimation error covariance is given by means of the induction method. Then, the desired estimator gain is calculated recursively by solving two sets of coupled matrix equations. Finally, two simulation examples are given to verify the usefulness of the strategy we proposed subject to the LAE under the improved accumulation-based ETM.

Keywords: Actuator fault; Improved accumulation-based event-triggered mechanism (ETM); Joint estimation; Networked systems; Recursive matrix equations.