Finite-Horizon Distributed H∞ State Estimation with Stochastic Parameters and Nonlinearities through Sensor Networks
This paper deals with the distributed H∞ state estimation problem for a class of discrete time-varying nonlinear systems with both stochastic parameters and stochastic nonlinearities. The system measurements are collected through sensor networks with sensors distributed according to a given topology. The purpose of the addressed problem is to design a set of time-varying estimators such that the average estimation performance of the networked sensors is guaranteed over a given finite-horizon. Through available output measurements from not only the individual sensor but also its neighboring sensors, a necessary and sufficient condition is established to achieve the H∞ performance constraint. The desired estimator parameters can be obtained by solving coupled backward recursive Riccati difference equations (RDEs). A numerical simulation example is provided to demonstrate the effectiveness and applicability of the proposed estimator design approach.
Discrete time-varying systems Distributed H∞ state estimation Recursive Riccati difference equations Sensor networks Stochastic nonlinearities Stochastic parameters
DING Derui WANG Zidong ZHANG Sunjie SHU Huisheng
School of Information Science and Technology, Donghua University, Shanghai 200051, China School of S School of Information Science and Technology, Donghua University, Shanghai 200051, China Department School of Information Science and Technology, Donghua University, Shanghai 200051, China
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
6508-6513
2012-07-01(万方平台首次上网日期,不代表论文的发表时间)