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

E. Gaura; R. Rider; N. Steele

doi:10.1007/3-540-45049-1_63

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

E. Gaura, R. Rider, N. Steele

College of Engineering, Environment & Science

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

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 language	English
Title of host publication	IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches
Editors	Rasiah Logananthara, Günther Palm, Moonis Ali
Publisher	Springer Verlag
Pages	534-542
Number of pages	9
Volume	1821
ISBN (Electronic)	978-3-540-45049-8
ISBN (Print)	978-3-540-67689-8
DOIs	https://doi.org/10.1007/3-540-45049-1_63
Publication status	Published - 2000
Event	The Thirteenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000 - New Orleans, United States Duration: 19 Jun 2000 → 22 Jun 2000

Conference

Conference	The Thirteenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000
Country/Territory	United States
City	New Orleans
Period	19/06/00 → 22/06/00

Access to Document

10.1007/3-540-45049-1_63

Cite this

Neural network based compensation of micromachined accelerometers for static and low frequency applications. / Gaura, E.; Rider, R.; Steele, N.
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 proceeding › Conference proceeding › peer-review

Gaura, E, Rider, R & Steele, N 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

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title = "Neural network based compensation of micromachined accelerometers for static and low frequency applications",

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. {\textcopyright} Springer-Verlag Berlin Heidelberg 2000.",

author = "E. Gaura and R. Rider and N. Steele",

year = "2000",

doi = "10.1007/3-540-45049-1_63",

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publisher = "Springer Verlag",

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AU - Steele, N.

PY - 2000

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N2 - 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.

AB - 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.

U2 - 10.1007/3-540-45049-1_63

DO - 10.1007/3-540-45049-1_63

M3 - Conference proceeding

SN - 978-3-540-67689-8

VL - 1821

SP - 534

EP - 542

BT - IEA/AIE 2000: Intelligent Problem Solving. Methodologies and Approaches

A2 - Logananthara, Rasiah

A2 - Palm, Günther

A2 - Ali, Moonis

PB - Springer Verlag

T2 - The Thirteenth International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2000

Y2 - 19 June 2000 through 22 June 2000

ER -

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

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