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The study on self-adaptive predictive arithmetic based on RBF neural network applied in the proportion control of hydrogen and nitrogen in synthesis ammonia production

机译:基于RBF神经网络的自适应预测算法在合成氨生产中氢氮比例控制中的研究

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Aim at the control questions of more interference factors, time-variant and oversize time delay in the proportion control of hydrogen and nitrogen in synthesis ammonia production, a self-adaptive predictive PID control scheme based on RBF neural network theory is presented, using ahead predictive to overcome large delay, and PID arithmetic based on RBF network to adjust the parameter of controller on-line. Results of simulation experiment show that this method has quick system response, strong adaptability and better robustness, it will be has wide perspective and practicability for the proportion of hydrogen and nitrogen in synthesis ammonia production.
机译:针对合成氨生产中氢和氮比例控制中干扰因素较多,时变和时延过大的控制问题,提出了基于RBF神经网络理论的自适应预测PID控制方案,并采用超前预测为克服较大的时延,采用基于RBF网络的PID算法在线调整控制器参数。仿真实验结果表明,该方法具有系统响应快,适应性强,鲁棒性强等优点,在合成氨生产中氢,氮比例具有广阔的应用前景。

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