Asynchronous distributed state estimation based on a continuous-time stochastic model

被引：3

作者：

Kowalczuk, Z. ^{[1
]}

Domzalski, M. ^{[1
]}

机构：

[1] Gdansk Univ Technol, Dept Decis Syst ETI, PL-80233 Gdansk, Poland

来源：

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING | 2012年 / 26卷 / 05期

关键词：

Gaussian processes; distributed systems; state estimation; Kalman filtering; KALMAN; MULTIRATE;

D O I：

10.1002/acs.1290

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, the problem of state estimation in an asynchronous distributed multi-sensor estimation (ADE) system is considered. In such an ADE system, the state of a plant of interest is estimated by a group of local estimators. Each local estimator based, for example, on a Kalman filter, performs fusion of data from its local sensor and other (remote) processors to compute possibly best state estimates. In performing data fusion, however, two important issues need to be addressed, namely, the problem of asynchronism of local processors and the one of unknown correlation between asynchronous data in local processors. Consequently, there are two main contributions proposed in this paper. The first is a method to deal with asynchronous discrete-time data based on a continuous-time stochastic plant model. The second contribution is an asynchronous distributed data-fusion algorithm. Simulated experiments illustrate the effectiveness of the proposed ADE approach. Copyright (c) 2011 John Wiley & Sons, Ltd.

引用

页码：384 / 399

页数：16

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