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Sensors 2018, 18(1), 217; https://doi.org/10.3390/s18010217

Introduction to State Estimation of High-Rate System Dynamics

1,2,†,* , 2,†
,
3,†
and
4,†
1
Applied Research Associates, Emerald Coast Division, Niceville, FL 32578, USA
2
Department of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA
3
Air Force Research Laboratory, Munitions Directorate, Eglin Air Force Base, FL 32542, USA
4
Energy Technologies and Materials, University of Dayton Research Institution, Dayton, OH 45469, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 8 November 2017 / Revised: 4 January 2018 / Accepted: 9 January 2018 / Published: 13 January 2018
(This article belongs to the Special Issue Sensors and Sensor Networks for Structural Health Monitoring)
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Abstract

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. View Full-Text
Keywords: adaptive observers; high-rate; state estimation; dynamics; structural health monitoring adaptive observers; high-rate; state estimation; dynamics; structural health monitoring
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Hong, J.; Laflamme, S.; Dodson, J.; Joyce, B. Introduction to State Estimation of High-Rate System Dynamics. Sensors 2018, 18, 217.

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