With reference to a real industrial application of process control, some considerations are discussed concerning the accuracy of methods for auto-tuning of proportional, integral and derivative factor (PID). In particular, a theoretical–experimental approach is described, that allows to evaluate the adequateness of new methods for auto-tuning of PID, able to significantly reduce the time duration for auto-tuning with respect to traditional ones. This result has been achieved by using suitable techniques of experimental data processing, based on neural-networks algorithms, set for this specific application. The effect on described methodology of environmental and operating disturbances is also described.

Use of neural networks for quick and accurate auto-tuning of PID controllers

D'EMILIA, Giulio
Membro del Collaboration Group
;
NATALE, EMANUELA
Membro del Collaboration Group
2007-01-01

Abstract

With reference to a real industrial application of process control, some considerations are discussed concerning the accuracy of methods for auto-tuning of proportional, integral and derivative factor (PID). In particular, a theoretical–experimental approach is described, that allows to evaluate the adequateness of new methods for auto-tuning of PID, able to significantly reduce the time duration for auto-tuning with respect to traditional ones. This result has been achieved by using suitable techniques of experimental data processing, based on neural-networks algorithms, set for this specific application. The effect on described methodology of environmental and operating disturbances is also described.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/21413
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