Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4944242 | Information Sciences | 2017 | 27 Pages |
Abstract
This paper investigates the Hâ filtering of Markov jump systems with general transition probabilities which are known, uncertain and unknown. The transmission from sensor to filter is determined by a mode-dependent event-triggered scheme. The advantage of the scheme is that no restriction is imposed on a triggering scalar. Employing a zero-order-holder, the resulting filtering error system is expressed by Markov jump systems with time delay. With the aid of a relaxed Lyapunov-Krasovskii functional and the Finlser lemma, the desired Hâ filter gains and the related triggering parameter are solved in a uniformed framework. It is shown that the proposed approach is less conservative than the existing one. Numerical examples are given to verify the validity of the proposed method.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Mouquan Shen, Dan Ye, Qing-Guo Wang,