Roll Speed and Roll Gap Control with Neural Network Compensation

スポンサーリンク

概要

• 論文の詳細を見る

• In this paper the detailed procedure of roll speed and roll gap control strategy development for a laboratory scale rolling mill is given. The core of the control strategy is the incorporation of feed-forward compensations based on neural network models for the roll force and roll torque, which are the major disturbances introduced during the rolling operation. An integrated computer simulation model is developed to investigate the performance of the proposed control strategies, and results show significant improvement over the traditional feedback control scheme. Based on the control strategies and the integrated simulation model, a major upgrading scheme is undertaken on an existing laboratory scale rolling mill. The new mill data acquisition and control systems, including the upgrading of the drive and gap motors, are currently under commissioning. After the mill upgrading system is fully commissioned, further work such as online adaptation of the neural network prediction model and the fine- adjustment of the feed-forward compensation need to be investigated for consistent control performance under changing rolling conditions.

• 社団法人 日本鉄鋼協会の論文
• 2005-06-15

著者

• Linkens D

  Institute For Microstructural And Mechanical Processing Engineering The University Of Sheffield

• Linkens D.

  Immpetus Department Of Automatic Control And Systems Engineering University Of Sheffield

• MAHFOUF M.

  IMMPETUS, Department of Automatic Control and Systems Engineering, The University of Sheffield

• YANG Y.

  IMMPETUS, Department of Automatic Control and Systems Engineering, The University of Sheffield

• GAMA M.

  IMMPETUS, Department of Automatic Control and Systems Engineering, The University of Sheffield

• Mahfouf M.

  Immpetus Department Of Automatic Control And Systems Engineering University Of Sheffield

• Gama M.

  Immpetus Department Of Automatic Control And Systems Engineering The University Of Sheffield

関連論文

• Fuzzy Model-based Charpy Impact Toughness Assessment for Ship Steels
• Roll Speed and Roll Gap Control with Neural Network Compensation
• Grain Growth Modelling for Continuous Reheating Process-A Neural Network-based Approach
• Roll Force and Torque Prediction Using Neural Network and Finite Element Modelling

スポンサーリンク