Robust energy-to-peak filtering for discrete-time nonlinear systems with measurement quantization

This paper investigates the problem of robust energy-to-peak filtering for a class of discrete-time systems with norm-bounded uncertain parameters, measurement quantization and Lipschitz nonlinearity. Assume that the system measurement output is quantized by a static, memoryless and logarithmic quantizer before it being transmitted to the filter, while the quantization errors can be treated as sector-bound uncertainties. Attention is focused on the design of a robust energy-to-peak filter to mitigate quantization effects and ensure the filtering error system is asymptotically stable with a prescribed energy-to-peak noise attenuation level. Sufficient conditions for the existence of such a energy-to-peak filter are expressed in terms of linear matrix inequalities (LMIs). A numerical example is presented to demonstrate the effectiveness of the proposed design method.