Closed-loop neural network controlled accelerometer

Elena Gaura, R. J. Rider, N. C. Steele

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The purpose of this paper is to present aspects of an integrated micromachined sensor-neural network transducer development. Micromachined sensors exhibit particular problems such as non-linear characteristics, manufacturing tolerances and the need for complex electronic circuitry. The novel transducer design described here, based on a mathematical model of the micromachined sensor, is aimed at improving in-service performance and facilitating design and manufacture over conventional transducers. The proposed closed-loop transducer structure incorporates two modular artificial neural networks: a compensating neural network, which performs a static mapping, and a feedback neural network, which both linearizes and demodulates the feedback signal. Simulation results to date show an excellent linearity, wide dynamic range and robustness to shocks for the proposed system. The design was approached from a control engineering perspective due to the closed-loop structure of the transducer.

Original languageEnglish
Pages (from-to)129-138
Number of pages10
JournalProceedings of the Institution of Mechanical Engineers. Part I: Journal of Systems and Control Engineering
Volume214
Issue number2
DOIs
Publication statusPublished - 2000
Externally publishedYes

Keywords

  • accelerometer
  • mechatronic
  • micromechanical devices
  • micromachined sensor
  • multilayer perceptron
  • neural network
  • CAPACITIVE ACCELEROMETER

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