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

P. A. Chertovskikh; A. V. Seredkin; O. A. Gobyzov; A. S. Styuf; M. G. Pashkevich; M. P. Tokarev

doi:10.1088/1742-6596/1359/1/012090

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

P. A. Chertovskikh, A. V. Seredkin, O. A. Gobyzov, A. S. Styuf, M. G. Pashkevich, M. P. Tokarev

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

3 Citations (Scopus)

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.

Original language	English
Article number	012090
Number of pages	6
Journal	Journal of Physics: Conference Series
Volume	1359
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/1359/1/012090
Publication status	Published - 21 Nov 2019
Event	4th All-Russian Scientific Conference Thermophysics and Physical Hydrodynamics with the School for Young Scientists, TPH 2019 - Yalta, Crimea, Ukraine Duration: 15 Sep 2019 → 22 Sep 2019

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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.",

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AU - Chertovskikh, P. A.

AU - Seredkin, A. V.

AU - Gobyzov, O. A.

AU - Styuf, A. S.

AU - Pashkevich, M. G.

AU - Tokarev, M. P.

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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.

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

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JO - Journal of Physics: Conference Series

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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

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

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