期刊
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
卷 65, 期 11, 页码 4816-4823出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2019.2958824
关键词
Noise measurement; Markov processes; Quantization (signal); Hidden Markov models; Switches; Packet loss; Markovian switching systems; multiple hierarchical structure; nonstationary filtering; quantization effect; repeated scalar nonlinear system
资金
- Basic Science Research Programs through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1A2B2004671]
- National Research Foundation of Korea [4220200113789] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This article addresses the quantized nonstationary filtering problem for networked Markov switching repeated scalar nonlinear systems (MSRSNSs). A more general issue is explored for MSRSNSs, where the measurement outputs are characterized by packet losses, nonstationary quantized output, and randomly occurred sensor nonlinearities (ROSNs) simultaneously. Note that both packet losses and ROSNSs are depicted by Bernoulli distributed sequences. By utilizing a multiple hierarchical structure strategy, the nonstationary filters are designed for MSRSNSs, in which the correlation among modes of systems, quantizer, and controller are presented in terms of nonstationary Markov process. A practical example is provided to verify the proposed theoretical results.
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