ABSTRACT
This chapter addresses the filtering problems for a class of discrete-time stochastic nonlinear time-delay systems with sensors information dropout and stochastic disturbances. It also addresses filter analysis and synthesis problems. The chapter illustrates the usefulness and flexibility of the filter design method developed. The measurement missing phenomenon is assumed to occur in a random way, and the missing probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval. The chapter aims to design a filter such that, for the admissible random measurement missing, stochastic disturbances, norm-bounded uncertainties as well as stochastic nonlinearities, the error dynamics of the filtering process is exponentially mean-square stable. By using the linear matrix inequality (LMI) method, sufficient conditions have been established that ensure the exponential mean-square stability of the filtering error, and then the filter parameters have been characterized by the solution to a set of LMIs.
