<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was developed. The network structure is based on solving this equation with respect to the input quantity when using the state variables. It is shown that such a real-time correction can be carried out using simple linear perceptrons. Due to the use of a neural technique, knowledge of the dynamic parameters of the transducer is not necessary. Theoretical considerations are illustrated by the results of simulation studies performed for the modeled second order transducer. The most important properties of the neural dynamic error correction, when emphasizing the fundamental advantages and disadvantages, are discussed.</p></abstract>

In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was developed. The network structure is based on solving this equation with respect to the input quantity when using the state variables. It is shown that such a real-time correction can be carried out using simple linear perceptrons. Due to the use of a neural technique, knowledge of the dynamic parameters of the transducer is not necessary. Theoretical considerations are illustrated by the results of simulation studies performed for the modeled second order transducer. The most important properties of the neural dynamic error correction, when emphasizing the fundamental advantages and disadvantages, are discussed.

Neural Network Based Real-time Correction of Transducer Dynamic Errors

Institute of Measurement Science, Electronics and Control, Silesian University of Technology, Gliwice, Poland

Measurement Science Review

{"article-title":"Neural Network Based Real-time Correction of Transducer Dynamic Errors"}

In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was...

Neural Network Based Real-time Correction of Transducer Dynamic Errors

Online veröffentlicht: 14. Jan. 2014

Seitenbereich: 286 - 291

DOI: https://doi.org/10.2478/msr-2013-0042

Schlüsselwörter
Artificial neural network, linear perceptron, dynamic errors correction, measuring transducer, state variables

This content is open access.

Neural Network Based Real-time Correction of Transducer Dynamic Errors

Online veröffentlicht: 14. Jan. 2014

Seitenbereich: 286 - 291

DOI: https://doi.org/10.2478/msr-2013-0042

SchlüsselwörterArtificial neural network, linear perceptron, dynamic errors correction, measuring transducer, state variables

This content is open access.

Schlüsselwörter
Artificial neural network, linear perceptron, dynamic errors correction, measuring transducer, state variables