Nonlinear Observers for Data Fusion based on Robustness norm for System with Delay and Missing Measurements.

Abstract

In this paper, H (H-Infinity, HI)-based nonlinear observers for continuous time dynamic system with state delay, and randomly missing measurements are presented. The Lyapunov energy (LE) functional to derive sufficient conditions for the local asymptotic stability for the observer-state error equations is derived. This observer’s performance with and without randomly missing measurements is evaluated by simulations carried out in MATLAB. The results validate the theoretical asymptotic behaviour of the proposed HI-based nonlinear observer. Then, the nonlinear observer is extended to nonlinear system with state delay and randomly missing measurements in the measurement data level (MLF) and state vector fusion (SVF) modes for multi-sensor data fusion (MSDF). It is ascertained that the derived theoretical result automatically extends to these nonlinear observers for data fusion due to their non-complicated structures.