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

E. Gaura, R. Rider, N. Steele, Ali M. Logananthara R. (Editor), Palm G. (Editor)

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

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. © Springer-Verlag Berlin Heidelberg 2000.
Original languageEnglish
Title of host publicationIEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches
EditorsRasiah Logananthara, Günther Palm, Moonis Ali
PublisherSpringer Verlag
Pages534-542
Number of pages9
Volume1821
ISBN (Electronic)978-3-540-45049-8
ISBN (Print)978-3-540-67689-8
DOIs
Publication statusPublished - 2000
EventThe Thirteenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000 - New Orleans, United States
Duration: 19 Jun 200022 Jun 2000

Conference

ConferenceThe Thirteenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000
CountryUnited States
CityNew Orleans
Period19/06/0022/06/00

Fingerprint

Accelerometers
Neural networks
Control nonlinearities
Compensation and Redress

Cite this

Gaura, E., Rider, R., Steele, N., Logananthara R., A. M. (Ed.), & G., P. (Ed.) (2000). Neural network based compensation of micromachined accelerometers for static and low frequency applications. In R. Logananthara, G. Palm, & M. Ali (Eds.), IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches (Vol. 1821, pp. 534-542). Springer Verlag. https://doi.org/10.1007/3-540-45049-1_63

Neural network based compensation of micromachined accelerometers for static and low frequency applications. / Gaura, E.; Rider, R.; Steele, N.; Logananthara R., Ali M. (Editor); G., Palm (Editor).

IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches. ed. / Rasiah Logananthara; Günther Palm; Moonis Ali. Vol. 1821 Springer Verlag, 2000. p. 534-542.

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

Gaura, E, Rider, R, Steele, N, Logananthara R., AM (ed.) & G., P (ed.) 2000, Neural network based compensation of micromachined accelerometers for static and low frequency applications. in R Logananthara, G Palm & M Ali (eds), IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches. vol. 1821, Springer Verlag, pp. 534-542, The Thirteenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000, New Orleans, United States, 19/06/00. https://doi.org/10.1007/3-540-45049-1_63
Gaura E, Rider R, Steele N, Logananthara R. AM, (ed.), G. P, (ed.). Neural network based compensation of micromachined accelerometers for static and low frequency applications. In Logananthara R, Palm G, Ali M, editors, IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches. Vol. 1821. Springer Verlag. 2000. p. 534-542 https://doi.org/10.1007/3-540-45049-1_63
Gaura, E. ; Rider, R. ; Steele, N. ; Logananthara R., Ali M. (Editor) ; G., Palm (Editor). / Neural network based compensation of micromachined accelerometers for static and low frequency applications. IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches. editor / Rasiah Logananthara ; Günther Palm ; Moonis Ali. Vol. 1821 Springer Verlag, 2000. pp. 534-542
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