Standard

An adaptive PID controller with an online auto-tuning by a pretrained neural network. / Chertovskikh, P. A.; Seredkin, A. V.; Gobyzov, O. A. et al.

In: Journal of Physics: Conference Series, Vol. 1359, No. 1, 012090, 21.11.2019.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Chertovskikh, PA, Seredkin, AV, Gobyzov, OA, Styuf, AS, Pashkevich, MG & Tokarev, MP 2019, 'An adaptive PID controller with an online auto-tuning by a pretrained neural network', Journal of Physics: Conference Series, vol. 1359, no. 1, 012090. https://doi.org/10.1088/1742-6596/1359/1/012090

APA

Chertovskikh, P. A., Seredkin, A. V., Gobyzov, O. A., Styuf, A. S., Pashkevich, M. G., & Tokarev, M. P. (2019). An adaptive PID controller with an online auto-tuning by a pretrained neural network. Journal of Physics: Conference Series, 1359(1), [012090]. https://doi.org/10.1088/1742-6596/1359/1/012090

Vancouver

Chertovskikh PA, Seredkin AV, Gobyzov OA, Styuf AS, Pashkevich MG, Tokarev MP. An adaptive PID controller with an online auto-tuning by a pretrained neural network. Journal of Physics: Conference Series. 2019 Nov 21;1359(1):012090. doi: 10.1088/1742-6596/1359/1/012090

Author

Chertovskikh, P. A. ; Seredkin, A. V. ; Gobyzov, O. A. et al. / An adaptive PID controller with an online auto-tuning by a pretrained neural network. In: Journal of Physics: Conference Series. 2019 ; Vol. 1359, No. 1.

BibTeX

@article{f292aad2c6b44043b504afc6461989ac,
title = "An adaptive PID controller with an online auto-tuning by a pretrained neural network",
abstract = "This paper describes an intelligent adaptive PID controller design procedure. The controller consists of a discrete time PID and an auto-tuning neural network unit. First system identification with a nonlinear autoregressive model (NARX) was performed. This model was then used to train the neural PID tuner. A special MATLAB toolbox {"}SmatPID Toolbox{"} was developed to automate the process of controller synthesis. The resulting controller was tested in a laboratory coal-gas furnace control system to track specified air flow rates.",
author = "Chertovskikh, {P. A.} and Seredkin, {A. V.} and Gobyzov, {O. A.} and Styuf, {A. S.} and Pashkevich, {M. G.} and Tokarev, {M. P.}",
year = "2019",
month = nov,
day = "21",
doi = "10.1088/1742-6596/1359/1/012090",
language = "English",
volume = "1359",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "1",
note = "4th All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2019 ; Conference date: 15-09-2019 Through 22-09-2019",

}

RIS

TY - JOUR

T1 - An adaptive PID controller with an online auto-tuning by a pretrained neural network

AU - Chertovskikh, P. A.

AU - Seredkin, A. V.

AU - Gobyzov, O. A.

AU - Styuf, A. S.

AU - Pashkevich, M. G.

AU - Tokarev, M. P.

PY - 2019/11/21

Y1 - 2019/11/21

N2 - This paper describes an intelligent adaptive PID controller design procedure. The controller consists of a discrete time PID and an auto-tuning neural network unit. First system identification with a nonlinear autoregressive model (NARX) was performed. This model was then used to train the neural PID tuner. A special MATLAB toolbox "SmatPID Toolbox" was developed to automate the process of controller synthesis. The resulting controller was tested in a laboratory coal-gas furnace control system to track specified air flow rates.

AB - This paper describes an intelligent adaptive PID controller design procedure. The controller consists of a discrete time PID and an auto-tuning neural network unit. First system identification with a nonlinear autoregressive model (NARX) was performed. This model was then used to train the neural PID tuner. A special MATLAB toolbox "SmatPID Toolbox" was developed to automate the process of controller synthesis. The resulting controller was tested in a laboratory coal-gas furnace control system to track specified air flow rates.

UR - http://www.scopus.com/inward/record.url?scp=85076473845&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1359/1/012090

DO - 10.1088/1742-6596/1359/1/012090

M3 - Conference article

AN - SCOPUS:85076473845

VL - 1359

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012090

T2 - 4th All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2019

Y2 - 15 September 2019 through 22 September 2019

ER -

ID: 22994138