Measurement Error Analysis of Autonomous Decentralized Load Tracking System

Measurement error analysis is presented for autonomous decentralized load tracking system. We propose a load tracking mechanism based on incomplete management of load information from subsystems. The system employs autonomous decentralized architecture, which enables online expansion and fault tolerance. Each subsystem asynchronously broadcasts load information to the data field shared by the subsystems. Load information in the data field is measured for a limited period of time to make the tracking ability efficient. The number of measurements and the estimation of total load from the measurements are stochastic variables. This paper shows the statistical model of measurement noise disturbing the tracking mechanism.