期刊
IEEE TRANSACTIONS ON SIGNAL PROCESSING
卷 60, 期 2, 页码 956-961出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSP.2011.2175224
关键词
Discrete-time systems; H-infinity filtering; networks; Markov chain; transition probability
资金
- Australian Research Council [DP1096780, DP0986376]
- Research Advancement Awards Scheme Program
- RDI at Central Queensland University, Australia [RDIM1109]
- Australian Research Council [DP0986376] Funding Source: Australian Research Council
This correspondence is concerned with network-based H-infinity filtering for discrete-time systems. The output signals of the system under consideration are transmitted to the filter through a constraint communication network, which usually leads to network-induced delays and packet dropouts. By introducing a logic data packet processor to choose the newest data signal from the network to actuate the filter, network-induced delays and packet dropouts are modeled as a Markov chain taking values in a finite set. As a result, the filter to be designed is modeled as a Markov jumping linear filter. By introducing some slack matrix variables in terms of probability identity, a less conservative bounded real lemma (BRL) is derived to ensure that the filtering error system is stochastically stable with a prescribed H-infinity level. Based on this BRL, suitable H-infinity filters are designed by employing a cone complementary approach. A practical example on the Leslie model about some certain pest's structured population dynamics is given to show the effectiveness of the proposed approach.
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