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以唐山钢铁股份有限公司第一、二钢轧厂的蓄热式钢包烘烤装置为控制对象,将基于RBF神经网络的PID控制方法与双交叉限幅方法结合引入到蓄热式钢包烘烤装置的温度控制中,实现了蓄热式钢包烘烤装置温度控制的节能优化。通过在Matlab环境下将RBF神经网络PID控制和传统的PID控制方法进行仿真研究,得出了最佳PID参数,将PID最佳参数应用到双交叉限幅控制方法中。仿真结果表明:基于RBF神经网络PID控制方法较传统的PID控制方法与双交叉限幅方法结合,其PID控制器快速性好,自适应力强,有更好的控制效果。并将该控制系统成功应用到唐山钢铁股份有限公司第一、二钢轧厂的蓄热式钢包烘烤装置温度控制中,在保证质量和产量的基础上,节省了混合煤气消耗量,使其节能32%。
Taking the regenerative ladle roasting device of the first and the second steel rolling mills of Tangshan Iron and Steel Co., Ltd. as the control object, the PID control method based on the RBF neural network and the double cross-limiting method are introduced into the regenerative ladle roasting device Of the temperature control, to achieve a regenerative ladle bake temperature control device optimization. By simulating RBF neural network PID control and traditional PID control method under Matlab environment, the best PID parameters are obtained, and the best parameters of PID are applied to the double cross limit control method. The simulation results show that the PID control method based on RBF neural network is more convenient than the traditional PID control method and double crossover clipping method. Its PID controller has good fastness, strong adaptability and better control effect. And the control system was successfully applied to the temperature control of the regenerative ladle bake plant of the first and second steel rolling mills of Tangshan Iron and Steel Co., Ltd., on the basis of ensuring the quality and output, saving the consumption of the mixed gas, Energy saving 32%.