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Title: Improved Auscultation with a Stethoscope Using Model Inversion for Unknown Input Estimation.


Abstract not provided.

Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
Personal time
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the 2016 American Control Conference held July 6-8, 2016 in Boston, MN.
Country of Publication:
United States

Citation Formats

Nelson, Garrett Dean, and Rajamani, Rajesh. Improved Auscultation with a Stethoscope Using Model Inversion for Unknown Input Estimation.. United States: N. p., 2016. Web. doi:10.1109/ACC.2016.7525533.
Nelson, Garrett Dean, & Rajamani, Rajesh. Improved Auscultation with a Stethoscope Using Model Inversion for Unknown Input Estimation.. United States. doi:10.1109/ACC.2016.7525533.
Nelson, Garrett Dean, and Rajamani, Rajesh. Fri . "Improved Auscultation with a Stethoscope Using Model Inversion for Unknown Input Estimation.". United States. doi:10.1109/ACC.2016.7525533.
title = {Improved Auscultation with a Stethoscope Using Model Inversion for Unknown Input Estimation.},
author = {Nelson, Garrett Dean and Rajamani, Rajesh},
abstractNote = {Abstract not provided.},
doi = {10.1109/ACC.2016.7525533},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Jul 01 00:00:00 EDT 2016},
month = {Fri Jul 01 00:00:00 EDT 2016}

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  • Sliding-mode observers are used to construct unknown input estimators. Then, these unknown input estimators are combined with sensor fault estimation schemes into one architecture that employs two sliding-mode observers for simultaneously estimating the plant’s actuator faults (part of the unknown input) and detecting sensor faults. Closed form expressions are presented for the estimates of unknown inputs and sensor faults. A benchmark example of a controlled inverted pendulum system from the literature is utilized in the simulation study. The study shows that the observers analyzed in this paper generate good estimates of the unknown input and sensor faults signals in noisymore » environments for nonlinear plants.« less
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  • Abstract not provided.