Distributed H∞ state estimation with stochastic parameters and nonlinearities through sensor networks: The finite-horizon case

Authors:
Derui Ding;Zidong Wang;Hongli Dong;Huisheng Shu
Affiliations:
School of Information Science and Technology, Donghua University, Shanghai 200051, China;School of Information Science and Technology, Donghua University, Shanghai 200051, China and Department of Information Systems and Computing, Brunel University, Uxbridge, Middlesex, UB8 3PH, UK;Research Institute of Intelligent Control and Systems, Harbin Institute of Technology, Harbin 150001, China;School of Information Science and Technology, Donghua University, Shanghai 200051, China
Venue:
Automatica (Journal of IFAC)
Year:
2012

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Abstract

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, and then the estimator design scheme is proposed via a certain H"2-type criterion. 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.