Title: An assessment of distributed state estimation

Authors: Magdi S. Mahmoud; Muhammad Sabih

Addresses: Systems Engineering Department, King Fahd University of Petroleum and Minerals, P.O. Box 5067, Dhahran 31261, Saudi Arabia ' Systems Engineering Department, King Fahd University of Petroleum and Minerals, P.O. Box 5067, Dhahran 31261, Saudi Arabia

Abstract: State estimation is an important topic in the study of dynamical systems. The problem of estimation can be structured into three categories: 1) centralised scheme; 2) decentralised scheme; 3) distributed scheme. Distributed estimation is a compromise between completely centralised and decentralised versions of estimation. In this paper, we will provide an assessment of distributed estimation based on Kalman filtering techniques for large-scale or sensor networks. In simulation, a second order dynamical system is employed in a scenario of ten sensor nodes. The sensor nodes attempt to estimate the states of the dynamical system with embedded consensus filters. The results show that the distributed estimation algorithm effectively approximates the central Kalman filter. It is concluded that the distributed estimation techniques for distributed dynamical system requires further extensive research.

Keywords: distributed systems; sensor networks; computer modelling; simulation; state estimation; dynamical systems; distributed estimation; Kalman filtering.

DOI: 10.1504/IJSCC.2013.055976

International Journal of Systems, Control and Communications, 2013 Vol.5 No.2, pp.93 - 107

Published online: 12 Jul 2014 *

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