H2 filter design for discrete-time Markov jump linear systems with partly unknown transition probabilities

2011 ◽  
Vol 33 (3) ◽  
pp. 318-337 ◽  
Author(s):  
Mouquan Shen ◽  
Guang-Hong Yang
Keyword(s):  
Linear Systems ◽  
Discrete Time ◽  
Filter Design ◽  
Transition Probabilities ◽  
Markov Jump ◽  
Jump Linear Systems ◽  
Partly Unknown Transition Probabilities ◽  
Markov Jump Linear Systems

Nonfragile H∞ Filtering of Continuous Markov Jump Linear Systems With General Transition Probabilities

2013 ◽  
Vol 135 (3) ◽  
Author(s):  
Mouquan Shen ◽  
Guang-Hong Yang
Keyword(s):  
Linear Systems ◽  
Filter Design ◽  
Transition Probabilities ◽  
Sufficient Conditions ◽  
Disturbance Attenuation ◽  
Linear Matrix ◽  
Markov Jump ◽  
Jump Linear Systems ◽  
Markov Jump Linear Systems ◽  
Stochastically Stable

This paper concerns the mode dependent H∞ filter design for continuous Markov jump linear systems. The filter gain to be designed is assumed to have additive variations and the transition probabilities are allowed to be known, uncertain with known bounds and unknown. Attention is focused on the design of a mode dependent nonfragile full order filter, which guarantees the filtering error system to be stochastically stable and has a prescribed H∞ disturbance attenuation performance. Sufficient conditions for the desired filter design are given in the framework of linear matrix inequality. If the filter gain variations become zero and the transition probabilities are completely known, the proposed method is reduced to the standard H∞ filtering results. A numerical examples is given to show the effectiveness of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document