TY - JOUR

T1 - Variance-constrained filtering for nonlinear systems with randomly occurring quantized measurements

T2 - recursive scheme and boundedness analysis

AU - Jia, Chaoqing

AU - Hu, Jun

PY - 2019/2/7

Y1 - 2019/2/7

N2 - In this paper, the robust optimal filtering problem is discussed for time-varying networked systems with randomly occurring quantized measurements via the variance-constrained method. The stochastic nonlinearity is considered by statistical form. The randomly occurring quantized measurements are expressed by a set of Bernoulli distributed random variables, where the quantized measurements are described by the logarithmic quantizer. The objective of this paper is to design a recursive optimal filter such that, for all randomly occurring uncertainties, randomly occurring quantized measurements and stochastic nonlinearity, an optimized upper bound of the estimation error covariance is given and the desired filter gain is proposed. In addition, the boundedness analysis problem is studied, where a sufficient condition is given to ensure the exponential boundedness of the filtering error in the mean-square sense. Finally, simulations with comparisons are proposed to demonstrate the validity of the presented robust variance-constrained filtering strategy.

AB - In this paper, the robust optimal filtering problem is discussed for time-varying networked systems with randomly occurring quantized measurements via the variance-constrained method. The stochastic nonlinearity is considered by statistical form. The randomly occurring quantized measurements are expressed by a set of Bernoulli distributed random variables, where the quantized measurements are described by the logarithmic quantizer. The objective of this paper is to design a recursive optimal filter such that, for all randomly occurring uncertainties, randomly occurring quantized measurements and stochastic nonlinearity, an optimized upper bound of the estimation error covariance is given and the desired filter gain is proposed. In addition, the boundedness analysis problem is studied, where a sufficient condition is given to ensure the exponential boundedness of the filtering error in the mean-square sense. Finally, simulations with comparisons are proposed to demonstrate the validity of the presented robust variance-constrained filtering strategy.

KW - Boundedness analysis

KW - Randomly occurring quantized measurements

KW - Time-varying nonlinear systems

KW - Variance-constrained filtering

U2 - 10.1186/s13662-019-2000-0

DO - 10.1186/s13662-019-2000-0

M3 - Article

AN - SCOPUS:85061235320

VL - 2019

JO - Advances in Difference Equations

JF - Advances in Difference Equations

SN - 1687-1839

IS - 1

M1 - 53

ER -