Abstract
In this paper, we consider the H ∞ filtering problem for linear systems using quantized measurements. The communication channel we consider consists of two cases: the ideal one and the unreliable one. For the ideal channel, we designed a filter to mitigate the quantization effects, which ensured not only the asymptotical stability but also a prescribed H ∞ filtering performance. For the unreliable channel, we introduced the stochastic variable satisfying Bernoulli random binary distribution to model the lossy measurements. We also designed a filter to cope with the losses and mitigate quantization effects simultaneously which ensured not only stochastic stability, but also a prescribed H ∞ filtering performance. Furthermore, we derive sufficient conditions for the existence of the above filters. Finally, a numerical example is given to illustrate that the proposed approach is effective and feasible.
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Lu, R., Li, H., Xue, A. et al. Quantized H ∞ Filtering for Different Communication Channels. Circuits Syst Signal Process 31, 501–519 (2012). https://doi.org/10.1007/s00034-011-9323-8
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DOI: https://doi.org/10.1007/s00034-011-9323-8