IEICE TRANSACTIONS on Fundamentals
A Neural-Net Based Controller Supplementing a Multiloop PID Control System
Summary :
In this paper, a design method of neural-net based PID controllers is proposed for multivariable nonlinear systems with mutual interactions. The proposed method adopt both a static pre-compensator and some multi-layered neural networks. The former is used for roughly decoupling the controlled object, and the latter is used in order to improve decoupling and to linearize the approximately decoupled controlled object. Also the design scheme based on the relationship between PID law and the generalized minimum variance control (GMVC) law is adopted. The effectivenes of the proposed control scheme is evaluated on a simulation example.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E85-A No.1 pp.256-261
- Publication Date
- 2002/01/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Systems and Control
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Makoto TOKUDA, Toru YAMAMOTO, "A Neural-Net Based Controller Supplementing a Multiloop PID Control System" in IEICE TRANSACTIONS on Fundamentals,
vol. E85-A, no. 1, pp. 256-261, January 2002, doi: .
Abstract: In this paper, a design method of neural-net based PID controllers is proposed for multivariable nonlinear systems with mutual interactions. The proposed method adopt both a static pre-compensator and some multi-layered neural networks. The former is used for roughly decoupling the controlled object, and the latter is used in order to improve decoupling and to linearize the approximately decoupled controlled object. Also the design scheme based on the relationship between PID law and the generalized minimum variance control (GMVC) law is adopted. The effectivenes of the proposed control scheme is evaluated on a simulation example.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e85-a_1_256/_p
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@ARTICLE{e85-a_1_256,
author={Makoto TOKUDA, Toru YAMAMOTO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Neural-Net Based Controller Supplementing a Multiloop PID Control System},
year={2002},
volume={E85-A},
number={1},
pages={256-261},
abstract={In this paper, a design method of neural-net based PID controllers is proposed for multivariable nonlinear systems with mutual interactions. The proposed method adopt both a static pre-compensator and some multi-layered neural networks. The former is used for roughly decoupling the controlled object, and the latter is used in order to improve decoupling and to linearize the approximately decoupled controlled object. Also the design scheme based on the relationship between PID law and the generalized minimum variance control (GMVC) law is adopted. The effectivenes of the proposed control scheme is evaluated on a simulation example.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - A Neural-Net Based Controller Supplementing a Multiloop PID Control System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 256
EP - 261
AU - Makoto TOKUDA
AU - Toru YAMAMOTO
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E85-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2002
AB - In this paper, a design method of neural-net based PID controllers is proposed for multivariable nonlinear systems with mutual interactions. The proposed method adopt both a static pre-compensator and some multi-layered neural networks. The former is used for roughly decoupling the controlled object, and the latter is used in order to improve decoupling and to linearize the approximately decoupled controlled object. Also the design scheme based on the relationship between PID law and the generalized minimum variance control (GMVC) law is adopted. The effectivenes of the proposed control scheme is evaluated on a simulation example.
ER -
English
