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目的设计综合反馈神经网络控制器,解决目前退火炉保温段温度均匀性控制方式的控制精度低,实时性差,均匀性控制效果不理想等问题.方法设计了一种动态响应快、抗干扰能力强、超调量小的基于RBF的综合反馈神经网络控制器,该控制器由控制网络和反馈网络组成,采用反馈控制系统结构,将控制网络的输出量作为反馈输入.结果使用反馈输入对整个控制网络各个烧嘴进行控制可使烧嘴之间更具有整体性,使温度均匀性控制效果更加理想.基于RBF的综合反馈神经网络控制器改善了系统多烧嘴控制的耦合特性,增强了烧嘴之间的关联性,提高了温度均匀性的控制水平,使系统的动态响应速度和稳态精度明显提高.结论解决了退火炉保温段温度均匀性控制难的问题,对提高系统运行速度,稳定和精度有重要作用.
Objective To design an integrated feedback neural network controller to solve the problems such as low control accuracy, poor real-time performance and unsatisfactory uniformity control in the current annealing furnace insulation control method.A method of designing a dynamic response with strong anti-interference ability , Small overshoot RBF-based integrated feedback neural network controller, the controller consists of a control network and feedback network, the use of feedback control system structure, the output of the control network as a feedback input.Results The use of feedback input to the entire control The control of each burner in the network can make the burners more integrated and make the temperature uniformity control effect more ideal.The RBF-based integrated feedback neural network controller improves the coupling characteristics of the system multi-burner control and enhances the burner , Which improves the control level of temperature uniformity and significantly improves the dynamic response speed and steady state accuracy of the system.Conclusion Solving the problem of difficult control of the temperature uniformity in the annealing section of the annealing furnace is of great importance to improving the system running speed and stability And precision has an important role.