AGC-ASC Decoupled Neural Networks Predictive Control Method
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摘要: 給出了板形板厚綜合控制模型,提出了基于TH神經網絡的動態矩陣設計方法并分析了其收斂特性.使用不變性原理對板形板厚綜系統進行了解耦設計,并對板形板厚解耦神經網絡預測控制系統,進行了仿真研究.結果表明神經網絡可在兒百ns的時間內達到穩定狀態,不僅滿足了軋鋼過程的快速性要求,而且控制精度也得到了提高.Abstract: The coupling models for the thickness-crown objects is established. A Dynamic Matrix Controller based on the TH neural networks is given with the conver-gence property. The computer simulations with the AGC-ASC decoupled neural networks predictive control system is complemented and it shows that the stable states of neural networks are reached with on more that one μs, this has not only satisfied the fast prop-erty of rolling process, but also obtained a higher control index.
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Key words:
- control/dynamic matrix control /
- neural networks /
- AGC-ASC synthetic system /
- convergence
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