Several Feed-forward Control Methods and their Comparison for the Thermal Power Plant Main Control System

• Eki Yurio

  Hitachi, Co., Ltd.

• Hirasawa Kotaro

  Kyusyu University

• Nomura Masahide

  Hitachi, Co., Ltd.

Bibliographic Information

Other Title

• 火力プラント主制御系の各種制御方式とその比較
• カリョク プラント シュセイギョケイ ノ カクシュ セイギョ ホウシキ ト ソ

Abstract

In thermal power plants, it is an important operation to improve the control accuracy of main steam pressure and temperature etc. during load up/down. This paper focused on temperature control that is most difficult to control due to the nonlinearity and long dead time of power plants. We applied some control methods such as MRAC, neural network and long range predictive control to the power plant main control system. Each method was evaluated by a simulator using detailed physical models that represents accurately the dynamics of power plants. We confirmed that each method is possible to control properly, but long range predictive control is better than other two methods. It is also stated that the thermal power plant is so complex that some consideration (persistently exiting condition, learning method of neural networks etc.) is necessary for the application of theoretical algorithm.

Journal

• IEEJ Transactions on Electronics, Information and Systems

  IEEJ Transactions on Electronics, Information and Systems 117 (3), 287-294, 1997

  The Institute of Electrical Engineers of Japan

Keywords

• ボイラ制御
• ニューラルネットワーク
• 火力プラント
• フィードフォワード制御
• 適応制御
• 予測制御
• プラント制御
• 温度制御
• シミュレーション

Details

• CRID: 1390001204607723648
• NII Article ID: 130006843627
• NII Article ID: 10002809668
• NII Book ID: AN10065950
• DOI: 10.1541/ieejeiss1987.117.3_287
• ISSN: 13488155
• ISSN: 03854221
• NDL BIB ID: 4149767
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I4149767
• Web Site: https://www.jstage.jst.go.jp/article/ieejeiss1987/117/3/117_3_287/_pdf
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• Abstract License Flag: Disallowed