Quantized filtering design for Markovian jump systems with defective mode information

Abstract

This paper is concerned with the problem of quantized H∞ filtering for a class of continuous-time Markovian jump linear systems with defective mode information. By virtue of a mode-dependent logarithmic quantizer, the measurement output of the plant is quantized, and the defective mode information in the Markov stochastic process simultaneously involves the exactly known, partially unknown and polytopic-type uncertain transition rates. By fully exploring the properties of transition rate matrices, together with the convexification of uncertain domains, a new quantized H∞ performance analysis criterion is first derived and then the filter synthesis is developed. It is shown that via a linearisation procedure, a unified framework can be developed such that both the full-order and reduced-order filters can be obtained by solving a set of linear matrix inequalities. Finally, an illustrative example is given to show the effectiveness of the proposed design method.