Robust Diagnosis of a DC Motor by Bond Graph Approach

Abstract

In this article, a Bond Graph (BG) approach is used for modeling, simulation and robust diagnosis of a DC Motor. The design and calculation of an observer is achieved by using graphical methods taking advantage of the structural properties of bond graph model. Simulation results are used to show the dynamic behavior of the system variables and assessing the performance of the observer. A modeling Bond Graph form Linear Fractional Transformations (BG-LFT) to generate constituted Analytical Redundant Relationship (ARR) two parts perfectly separated: A nominal portion denotes the residual and an uncertain part, which serves both to the calculation of adaptive thresholds for normal operation and to sensitivity analysis.