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中文摘要：
采用小波函数作为模糊隶属函数，将模糊控制与神经网络相结合，利用神经网络实现模糊推理．针对BP算法易陷入局部极值点的缺点和简单遗传算法局部搜索能力差的不足，提出了一种混合学习算法，即首先利用遗传算法全局搜索的特点来离线优化神经网络的参数，再利用BP算法较强的局部搜索能力对网络参数进行在线调整．仿真结果表明，该网络能对不同的对象实施有效控制，且具有快速、适应性强等特点．
英文摘要：
Using wavelet basis function as membership function, fuzzy control and neural network were combined, and the fuzzy inference was realized by neural network. To counteract the defects of BP algorithm and the chances of simple genetic algorithm premature convergence, a hybrid learning algorithm was proposed. First, the genetic algorithm was used to optimize the fuzzy neural network＇ s parameters off-line. Then, because of the strong capability of local search, the BP algorithm was used to adjust the parameters on-line. The simulation results showed that the network could control different objects effectively, and had the characteristics of speediness and adaptability.
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