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Research of wheat dampening MPC system based on RBF neural network algorithm

机译:基于RBF神经网络算法的小麦衰减MPC系统研究

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For the nonlinear time delay features that exists in the wheat watering system of flour production industrial processes control, according to the RBF Neural Network (RBFNN) that has approaching any complicated nonlinear function relations and strong pattern recognition ability traits, the paper presents a dampening of wheat DMC system on the basic of RBFNN. The nonlinear model that has been identified by RBFNN is as the predictive model in the paper. Finally, the simulation results show that this method has good dynamic characteristics and robustness, it can take effective control of wheat dampener.
机译:对于面粉生产工业过程中存在的小麦浇水系统中存在的非线性时间延迟特征,根据RBF神经网络(RBFNN),具有接近任何复杂的非线性函数关系和强大的模式识别能力特征,纸张呈现了湿度小麦DMC系统在RBFNN的基础上。 RBFNN识别的非线性模型作为纸张中的预测模型。最后,仿真结果表明,该方法具有良好的动态特性和鲁棒性,可以有效地控制小麦湿膜。

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