Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4974708 | Journal of the Franklin Institute | 2015 | 28 Pages |
Abstract
This paper concerns the Hâ filtering of Markov jump nonlinear systems with general uncertain transition probabilities allowed to be uncertain and unknown. Attention is focused on the construction of an extended filter such that the filtering error system is stochastically stable with a prescribed Hâ performance requirement. Effective strategies are developed to deal with nonlinearities induced by uncertain and unknown transition probabilities and system nonlinearities, which is also the main contribution of this work. Based on these strategies, sufficient conditions to render the filtering error systems stochastic stable with the prescribed Hâ performance are established in the framework of linear matrix inequalities. The validity of the proposed filtering scheme is illustrated by numerical examples.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Mouquan Shen, Ju H. Park, Dan Ye,