Design of a Self-Tuning PID Control System by Neural Networks
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- Aoyama Takeo
- Osaka Prefecture University
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- Omatu Sigeru
- Osaka Prefecture University
Bibliographic Information
- Other Title
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- ニューラルネットワークによるセルフチューニングPID制御系の設計
- ニューラル ネットワーク ニヨル セルフ チューニング PID セイギョケイ
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Description
In Japan, about 84 percent of real plants adopts PID controllers. However, when we use the PID controllers, it generally needs much effort and time to tune PID gains. In this paper, we propose a method to tune the PID gains by using three-layered neural networks. Taking into consideration that the PID gains are non-negative real number, we select functions whose derivatives are sigmoid as output functions in the output layer. To find system's Jacobian, we identify the unknown plant by using a neural network as an emulator. Finally, numerical results are illustrated to show effectiveness of the present method through simulations.
Journal
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- IEEJ Transactions on Electronics, Information and Systems
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IEEJ Transactions on Electronics, Information and Systems 116 (11), 1197-1201, 1996
The Institute of Electrical Engineers of Japan
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Keywords
Details 詳細情報について
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- CRID
- 1390001204608260352
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- NII Article ID
- 10009587538
- 130006844048
- 10001787115
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- NII Book ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL BIB ID
- 4067404
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed