Distributed Sampled-Data Nonfragile Consensus Filtering Over Sensor Networks With Topology Switching and Transmission Delay
Xiangli Jiang, Guihua Xia, Zhiguang Feng, Xingjian Jing
Abstract
This article concerns the distributed sampled-data nonfragile consensus filter design for a continuous-time linear system with respect to exogenous disturbance. A network of sensor nodes is employed to monitor the plant. The information from each sensor node and its neighbors is aperiodically sampled while collaboratively transmitted in the network, where the phenomena of switching directed topologies and network-induced transmission delay are unavoidably existent. The estimated state of the plant at each node is updated by a consensus of state estimates from its neighbors. By acquiring the sensor output measurement, a Luenberger-type filter is constructed not only to provide robustness against some level of filter gain perturbations, but also to guarantee the asymptotic stability of the resultant filtering error system with an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_{\infty }$</tex-math></inline-formula> performance requirement. Based on algebraic graph theory, nonfragile synthesis technique and Lyapunov–Krasovskii functional method, the filter parameters are characterized in terms of some feasible solutions to certain linear matrix inequalities. The theoretical analysis is validated by numerical simulations.