Closed-loop, neural network controlled accelerometer design

E.I. Gaura, N. Ferreira, R.J. Rider, N. Steele, Romanowicz B. Laudon M. (Editor)

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

2 Citations (Scopus)

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
PublisherNSTI
Pages513-516
Number of pages4
Publication statusPublished - 2000
EventInternational Conference on Modeling and Simulation of Microsystems - San Diego, United States
Duration: 27 Mar 200029 Mar 2000
http://www.nsti.org/Nanotech2000/MSM2000/

Conference

ConferenceInternational Conference on Modeling and Simulation of Microsystems
Abbreviated titleMSM
CountryUnited States
CitySan Diego
Period27/03/0029/03/00
Internet address

Fingerprint

Multilayer neural networks
Accelerometers
Transducers
Neural networks
Feedback
Controllers
Sensors

Keywords

  • Accelerometers
  • Closed loop control systems
  • Electrostatic actuators
  • Feedback control
  • Machine design
  • Microelectromechanical devices
  • Micromachining
  • Nonlinear systems
  • Robustness (control systems)
  • Transducers, Electrostatic actuation
  • Micromachined accelerometers
  • Model reference control
  • Multilayer perceptron (MLP) neural networks, Neural networks

Cite this

Gaura, E. I., Ferreira, N., Rider, R. J., Steele, N., & Laudon M., R. B. (Ed.) (2000). Closed-loop, neural network controlled accelerometer design. In 2000 International Conference on Modeling and Simulation of Microsystems (pp. 513-516). NSTI.

Closed-loop, neural network controlled accelerometer design. / Gaura, E.I.; Ferreira, N.; Rider, R.J.; Steele, N.; Laudon M., Romanowicz B. (Editor).

2000 International Conference on Modeling and Simulation of Microsystems. NSTI, 2000. p. 513-516.

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

Gaura, EI, Ferreira, N, Rider, RJ, Steele, N & Laudon M., RB (ed.) 2000, Closed-loop, neural network controlled accelerometer design. in 2000 International Conference on Modeling and Simulation of Microsystems. NSTI, pp. 513-516, International Conference on Modeling and Simulation of Microsystems, San Diego, United States, 27/03/00.
Gaura EI, Ferreira N, Rider RJ, Steele N, Laudon M. RB, (ed.). Closed-loop, neural network controlled accelerometer design. In 2000 International Conference on Modeling and Simulation of Microsystems. NSTI. 2000. p. 513-516
Gaura, E.I. ; Ferreira, N. ; Rider, R.J. ; Steele, N. ; Laudon M., Romanowicz B. (Editor). / Closed-loop, neural network controlled accelerometer design. 2000 International Conference on Modeling and Simulation of Microsystems. NSTI, 2000. pp. 513-516
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