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Optimization of a fuzzy controller using neural network

机译:基于神经网络的模糊控制器优化

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This paper presents a strategy for optimization of a fuzzy logic controller based on a control scheme, which consists of a fuzzy logic controller and a conventional derivative controller. For this purpose, we first choose a set of membership functions regarding change-in-error e/spl dot/, which represent the feedback of velocity. Then we optimize them using neural network in self-organizing process. To demonstrate the effectiveness of the proposed method, we report a number of simulation results involving both step and tracking control of a nonlinear plant.
机译:本文提出了一种基于控制方案的模糊逻辑控制器优化策略,该方案由模糊逻辑控制器和常规的微分控制器组成。为此,我们首先选择一组关于误差变化e / spl dot /的隶属函数,它们代表速度的反馈。然后我们在自组织过程中使用神经网络对其进行优化。为了证明所提出方法的有效性,我们报告了许多仿真结果,涉及非线性工厂的步进控制和跟踪控制。

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