【摘要】 给出了一种基于模糊神经网络的模型参考自适应控制方案,首先,构造了一种运用递推预报误差（RPE）算法的多层前向神经网络,并用其对被控对象建模,然后,又构造了一种模糊神经网络控制器（FNNC）,从而为一类难以建立精确数学模型的非线性被控对象提供了一种新的自适应控制方法,仿真结果验证了其有效性,更多还原

【Abstract】 This paper presents a model reference adaptive control based on fuzzy neural network,First,we design a multilayer feedforward neural network using recursive prediction error (RPE)algorithms and use it to identify the model of the controled object,Then,we design a fuzzy neural network controller (FNNC),So we supply a kind of new adaptive method for a sort of nonlinear controlled object for which it is difficult to build the precisemath model,The simulation verifies its validity,更多还原