【摘 要】
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The hot rolled strip laminar cooling system is a complex industrial process,associated with features of strong nonlinear and changing operating conditions.So,the process is hard to control with tradit
【机 构】
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School of Information and Control engineering,Shenyang Jianzhu University,Shenyang,110168,China;Key
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The hot rolled strip laminar cooling system is a complex industrial process,associated with features of strong nonlinear and changing operating conditions.So,the process is hard to control with traditional close loop control methods.But fortunately,there is the repeated characteristic in the laminar cooling process,which is very suited to apply the iterative learning between the strips.So,PI iterative learning method is proposed in this paper to learn the inner knowledge between the strips with similar working condition.On the other hand,in order to improve the control effect,CBR(case-based reasoning)technology is applied to adjust the parameters P and I according to the changing working conditions.The experiments are conducted with industrial operating data.The results show that,with the proposed method,it is effective to find the right operating point quickly and the strip coiling temperature can be controlled in the suitable range.
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