×

Distributed estimation for parameter in heterogeneous linear time-varying models with observations at network sensors. (English) Zbl 1346.93360

Summary: In this paper, a distributed stochastic approximation based estimation algorithm is proposed to estimate the parameter in heterogeneous linear time-varying models associated with sensors from a network. At any time, each agent updates its estimate using the local observations and the information derived from its neighboring agents. The estimates are shown to converge to the one that minimizes the long run average of the square residuals. Switch of the communication graphs is assumed to be deterministic, and the regressors of the linear models are assumed to satisfy some ergodic property, rather than the conditional independence or strict stationarity. Numerical simulations are given to illustrate the obtained theoretic result.

MSC:

93E10 Estimation and detection in stochastic control theory
93C05 Linear systems in control theory
93A14 Decentralized systems
94C15 Applications of graph theory to circuits and networks
PDFBibTeX XMLCite
Full Text: DOI