Abstract
This paper considers the problem of H∞ filtering for uncertain discrete-time systems with quantized measurements and packet dropouts. The time-invariant uncertain parameters are supposed to reside in a polytope. The system measurement outputs are quantized by a memoryless logarithmic quantizer before being transmitted to the filter and the performance of packet dropouts is described by Bernoulli random binary distribution. Attention is focused on the design of H∞ filter to mitigate the effects of quantization and packet dropouts, which ensured not only stochastically stability but also a prescribed H∞ noise attenuation level. Via parameter-dependent Lyapunov function approach and introducing some slack variables, sufficient conditions for the existence of an H∞ filter are expressed in terms of linear matrix inequalities (LMIs). Two examples are provided to demonstrate the effectiveness and applicability of the proposed method.
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