Affiliation:
1. School of Electronic Engineering, Heilongjiang University, Harbin 150080, China
2. Key Laboratory of Information Fusion Estimation and Detection, Harbin 150080, China
Abstract
In estimation of linear systems, an efficient event-triggered Kalman filter algorithm is proposed. Based on the hypothesis test of Gaussian distribution, the significance of the event-triggered threshold is given. Based on the threshold, the actual trigger frequency of the estimated system can be accurately set. Combining the threshold and the proposed event-triggered mechanism, an event-triggered Kalman filter is proposed and the approximate estimation accuracy can also be calculated. Whether it is a steady system or a time-varying system, the proposed algorithm can reasonably set the threshold according to the required accuracy in advance. The proposed event-triggered estimator not only effectively reduces the communication cost, but also has high accuracy. Finally, simulation examples verify the correctness and effectiveness of the proposed algorithm.
Funder
National Natural Science Foundation (NNSF) of China
University Basic Research Foundation of Heilongjiang Province
Outstanding Youth Foundation of Heilongjiang University
Key Laboratory of Information Fusion Estimation and Detection, Heilongjiang Province
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献