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首页> 外文期刊>Annals of nuclear energy >APPLICATION OF A FUZZY LEARNING ALGORITHM TO NUCLEAR STEAM GENERATOR LEVEL CONTROL
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APPLICATION OF A FUZZY LEARNING ALGORITHM TO NUCLEAR STEAM GENERATOR LEVEL CONTROL

机译：模糊学习算法在核汽轮机液位控制中的应用

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摘要

In order to reduce the load of tuning works by trial-and-error for obtaining the best control performance of conventional fuzzy control algorithm, a fuzzy control algorithm with learning function is investigated in this work. This fuzzy control algorithm can make its rule base and tune the membership functions automatically by use of learning function which needs the data from the control actions of the plant operator or other controllers such as PI controller. Learning process in fuzzy control algorithm is to find the optimal values of parameters, which consist of the membership functions and the rule base, by gradient descent method. Learning speed of gradient descent is significantly improved in this work with the addition of modified momentum term. This control algorithm is applied to the steam generator level control by computer simulations. The simulation results confirm the good performance of this control algorithm for level control and show that the fuzzy learning algorithm has the generalization capability for the relation of inputs and outputs and it also has the excellent capability of disturbance rejection.
机译：为了通过反复试验来减轻调优工作的负担，以获得常规模糊控制算法的最佳控制性能，本文研究了一种具有学习功能的模糊控制算法。这种模糊控制算法可以通过使用学习功能来建立规则库并自动调整隶属度，学习功能需要工厂操作员或其他控制器（例如PI控制器）的控制动作中的数据。模糊控制算法的学习过程是通过梯度下降法找到由隶属度函数和规则库组成的参数的最优值。通过添加修改的动量项，可以显着提高梯度下降的学习速度。通过计算机仿真将该控制算法应用于蒸汽发生器的液位控制。仿真结果证实了该控制算法在液位控制中的良好性能，表明模糊学习算法具有输入输出关系的泛化能力，并且具有优异的抗干扰能力。

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