Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7151817 | Systems & Control Letters | 2014 | 9 Pages |
Abstract
This paper is concerned with the model reduction problem for Markovian jump systems with partly known transition probabilities. By making use of an existing result on the convex properties of the transition probabilities, an improved condition is first derived for the Hâ performance analysis of the error system. Two different approaches, one in terms of linear matrix inequalities (LMIs) and another in the form of an iterative algorithm subject to LMI constraints, are then proposed to find a reduced-order model such that the Hâ performance of the error system is bounded by a specified level. The first approach is obtained using Finsler's Lemma, and involves fewer decision variables than the existing method. It is shown that the proposed methods cover some existing results as special cases. Finally, the advantages of our results are clearly illustrated by a numerical example.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Xianwei Li, James Lam, Huijun Gao, Ping Li,