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鋼包精煉爐的電極系統智能建模及控制

Intelligent Modeling and Control Strategy for the Electrode System in Ladle Furnance

  • 摘要: 針對鋼包精煉爐電極控制系統具有非線性、時變、模型不確定、大滯后、多輸入多輸出耦合的特點,提出一種基于神經網絡實時在線辯識的內模控制方案.控制器采用神經網絡解耦,將混沌機制引入到BP算法中,用以加快學習的收斂速度.仿真結果證實了控制策略的有效性.

     

    Abstract: In accordance with such characters of the electrode control system in ladle furnace as the high non-linearity, time-variant, uncertainty of the model, output response time delay serious, and multivariable input and output coupling, an internal model control strategy based on real-time identification on line by neural network was presented. The control strategy applies neural network decoupline control and the chaos algorithm to the improved BP algorithm and speeds up the training of neural network. The validity of the control strategy is verified by simulation analysis.

     

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