Closed-loop, neural network controlled accelerometer design

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

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

Abstract

In this paper, a closed-loop, smart transducer design is proposed, based on artificial neural network (ANN) techniques. The design aims to improve the performance of open-loop, off-the-shelf capacitive acceleration sensors and increase their robustness to manufacturing tolerances. A "model reference" control strategy was adopted for the design of the smart transducer. Multilayer perceptron (MLP) type networks were chosen for implementing the control strategy. While a static MLP was used for the feedback arrangement, a tap delayed lines MLP was necessary for implementing the controller due to the dynamic nonlinear behaviour exhibited, by the sensing device. A dynamic version of the back-error propagation algorithm was used for training the networks. The resulting closed-loop transducer had a dynamic range of +/-10g and a stable behaviour for input stimuli up to +/-100g.

Original languageEnglish
Title of host publication2000 International Conference on Modeling And Simulation of Microsystems, Technical Proceedings
EditorsM Laudon, B Romanowicz
PublisherComputational Publications
Pages513-516
Number of pages4
ISBN (Print)0966613570
Publication statusPublished - 2000
Externally publishedYes
Event3rd International Conference on Modeling and Simulation of Microsystems - San Diego, Canada
Duration: 27 Mar 200029 Mar 2000

Conference

Conference3rd International Conference on Modeling and Simulation of Microsystems
CountryCanada
CitySan Diego
Period27/03/0029/03/00

Keywords

  • micromachined accelerometer
  • neural network
  • model reference control

Cite this

Gaura, E., Ferreira, N., Rider, R. J., & Steele, N. C. (2000). Closed-loop, neural network controlled accelerometer design. In M. Laudon, & B. Romanowicz (Eds.), 2000 International Conference on Modeling And Simulation of Microsystems, Technical Proceedings (pp. 513-516). Computational Publications.