Neural network based compensation of micromachined accelerometers for static and low frequency applications

Elena Gaura, R. J. Rider, N Steele

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

In this work, a single-shot direct inverse compensation procedure based on neural networks is proposed, with application to micromachined accelerometers. Compensation was first considered from an empirical viewpoint to determine whether or not some kind of relationship exists between the severity of different nonlinearities and the complexity of the network required to control such nonlinearities. The procedure was then validated by applying direct inverse control to the measured static characteristic of a micromachined acceleration sensing element.

Original languageEnglish
Title of host publicationIntelligent Problem Solving. Methodologies and Approaches
Subtitle of host publication13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000 New Orleans, Louisiana, USA, June 19–22, 2000 Proceedings
EditorsRasiah Loganantharaj, Gunther Palm, Moonis Ali
Place of PublicationBerlin; New York
PublisherSpringer, Springer Nature
Pages534-542
Number of pages9
ISBN (Print)3540676899
DOIs
Publication statusPublished - 2000
Externally publishedYes
Event13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2000) - NEW ORLEANS
Duration: 19 Jun 200022 Jun 2000

Publication series

NameLecture Notes in Artificial Intelligence
PublisherSpringer-Verlag Berlin
Volume1821
ISSN (Print)0302-9743

Conference

Conference13th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2000)
CityNEW ORLEANS
Period19/06/0022/06/00

Keywords

  • SYSTEMS

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