Work

Recursive Strong Tracking Filtering for Power Harmonic Detection With Outliers-Resistant Event-Triggered Mecha-nism

Year: 2024

Type: article

Abstract: This paper is concerned with the problem of power harmonic detection subject to communication resource constraints and measurement outliers. A dynamic tracking model is established to capture the dynamics of harmonic signals considering that the underlying system is subject to multiplicative noises, additive noises and outliers. Furthermore, an outlier-resistant event-triggered mechanism is designed to prevent the transmission of unnecessary measurements and outliers. In order to guarantee the satisfactory filtering performance, this paper aims to design a recursive strong tracking filtering algorithm under the event-triggered mechanism, where an upper bound on the filtering error covariance matrix is obtained by solving a set of Riccati difference equations, and minimized to recursively compute the filter gain matrix. Finally, the effectiveness of the proposed algorithm is verified through carrying out two sets of simulations.

Source: International Journal of Network Dynamics and Intelligence

DOI: 10.53941/ijndi.2024.100023

Authors: Xingzhen Bai, Guhui Li, Mingyu Ding, Liqun Yu, Yufeng Sun

Institutions: Shandong University of Science and Technology, State Grid Corporation of China (China)

Language: English

Topic: Power Quality and Harmonics

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

Funder: National Natural Science Foundation of China

Award: G6750264081