Robust H∞ fusion filtering for discrete-time nonlinear delayed systems with missing measurement
This paper explores the problem of multi-sensor robust H∞ fusion filtering for a class of discrete-time stochastic nonlinear systems with missing measurement and time delays. This discrete-time nonlinear system model is composed of a linear dynamic system and a bounded static nonlinear operator. The missing measurements from multi-sensors are described by a binary switching sequence that obeys a conditional probability distribution. By employing the Lyapunov-Krasovskii functional method with the stochastic analysis approach, a centralized fusion filter is designed such that, for all possible missing observations, the fusion error systems is globally asymptotically stable in the mean square, and the prescribed H∞ performance constraint is met. A simulation example is provided to illustrate the design procedure and expected performance.