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提出了一种基于遗传算法的模糊网络控制系统，该系统采用模糊神经网络结构实现，它用遗传算法优化具有全局性的隶属函数参数，而用ＢＰ算法调节和优化具有局部性的网络权值参数。仿真结果表明该控制器可大大提高模糊神经推理控制系统的自学习性和鲁棒性。
A fuzzy neural network control system based on genetic algorithm is proposed. The system adopts fuzzy neural network structure. Genetic algorithm is used to optimize the global membership functions. BP algorithm is used to adjust and optimize the local network weight parameters . The simulation results show that the controller can greatly improve the self-learning and robustness of fuzzy neural reasoning control system.