基于CMAC神经网络的工业过程稳态优化

Steady-State Optimization of Industrial Processes Based on CMAC Neural Network

  • 摘要: 提出一种利用 CMAC(cerebellar m odel articulation controller)神经网络进行工业过程的辨识和稳态优化方法 .利用 CMAC神经网络的优点 ,基于系统的动态信息 ,在不干扰系统正常运行的情况下获得当前时刻下系统的稳态模型 ,并在此模型的基础上 ,对系统进行稳态优化和仿真 .仿真结果证明了该方法的有效性

     

    Abstract: A kind of identification and steady state optimization method based on CMAC (cerebellar model articulation controller) neural network to industrial process is proposed. The method makes use of the advantage of CMAC neural network and considers dynamic information of the system to obtain steady state model without interfering on the formal operation of the system. Based on the model, steady state of the system is optimized. The result of simulation proves the effectiveness of the method.

     

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