Abstract
The paper is discussed with the problem of finite‐time H∞ filtering for discrete‐time singular Markovian jump systems (SMJSs). The systems under consideration consist of time‐varying delay, actuator saturation and partly unknown transition probabilities. We pay attention to the design of a H∞ filtering which ensures the filtering error systems to be singular stochastic finite‐time boundedness. By employing an adequate stochastic Lyapunov functional together with a class of linear matrix inequalities (LMIs), a sufficient condition is firstly established, which guarantees the systems to achieve our goal and satisfy a prescribed H∞ attenuation level in the given finite‐time interval. Considering the above conditions, a distinct presentation for the requested H∞ filter is given. Finally, two numerical examples add to a dynamical Leontief model of economic systems are presented to illustrate the validity of the developed theoretical results.
Highlights
IntroductionSignal estimation has received remarkable attention in the field of control, as an elementary problem in signal processing
Over the past decades, signal estimation has received remarkable attention in the field of control, as an elementary problem in signal processing
As is known to all, the traditional Kalman filtering [1] is the most popular ways to deal with the signal estimation
Summary
Signal estimation has received remarkable attention in the field of control, as an elementary problem in signal processing. As far as we know, the problem about discrete finite-time H∞ filtering for stochastic systems has less been researched, so that it promotes the main purpose of our study. Ma and Chen [45] presented singular TS fuzzy time-varying delay systems with actuator saturation for the problem of memory dissipative control. We investigates the finite-time H∞ filter design for discrete-time SMJSs with time-varying delay, partly unknown transition probabilities and actuator saturation. We use T stands for matrix transposition or vector and ∗ stands for the transposed elements in the symmetric positions of a matrix
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