@article {10.3844/jmrsp.2019.42.51,
article_type = {journal},
title = {New Model-Based Fault Detection Approach using Black Box Observer},
author = {Eissa, M. Abdullah and Darwish, R. R. and Bassiuny, A. M.},
volume = {3},
year = {2019},
month = {Mar},
pages = {42-51},
doi = {10.3844/jmrsp.2019.42.51},
url = {https://thescipub.com/abstract/jmrsp.2019.42.51},
abstract = {Most of the emerging engineering systems lack the presence of explicit physical insights or prior knowledge that clearly depicts the model. In such cases, the conventional observer-based fault detection is difficult to be employed because of its observer gain tuning. Herein, black box behaviors arose as a promising trend that could overcome those challenges that appears due to lacking the physical insights. Thus, this work targeted designing a reliable observer based on black box concept. The proposed observer design considers observer gain tuning, regardless the mathematical representation of the plant. Extensive simulation work has been conducted in order to verify the effectiveness of the proposed black box observer design. The results performed on DC motor advocate that the proposed black box observer operates with significantly better performance than conventional counterparts’ methodologies.},
journal = {Journal of Mechatronics and Robotics},
publisher = {Science Publications}
}