{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T18:23:11Z","timestamp":1790706191581,"version":"4.1.0"},"reference-count":95,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,1,13]],"date-time":"2018-01-13T00:00:00Z","timestamp":1515801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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\u2019s 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.<\/jats:p>","DOI":"10.3390\/s18010217","type":"journal-article","created":{"date-parts":[[2018,1,15]],"date-time":"2018-01-15T12:30:36Z","timestamp":1516019436000},"page":"217","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":44,"title":["Introduction to State Estimation of High-Rate System Dynamics"],"prefix":"10.3390","volume":"18","author":[{"given":"Jonathan","family":"Hong","sequence":"first","affiliation":[{"name":"Applied Research Associates, Emerald Coast Division, Niceville, FL 32578, USA"},{"name":"Department of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Laflamme","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction, and Environmental Engineering, Iowa State University, Ames, IA 50011, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob","family":"Dodson","sequence":"additional","affiliation":[{"name":"Air Force Research Laboratory, Munitions Directorate, Eglin Air Force Base, FL 32542, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bryan","family":"Joyce","sequence":"additional","affiliation":[{"name":"Energy Technologies and Materials, University of Dayton Research Institution, Dayton, OH 45469, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,13]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Microsecond prognostics and health management","volume":"60","author":"Lowe","year":"2014","journal-title":"IEEE Reliab. 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